JP5157084B2 - Correlation calculation device, focus detection device, and imaging device - Google Patents

Description

  The present invention relates to a correlation calculation method and a correlation calculation device for calculating the correlation of a plurality of signal data strings, and a focus detection device and an imaging device using them.

  There is known an apparatus that forms a light image of a target object on a pair of photoelectric conversion element arrays, and calculates a correlation between a pair of electric signal data strings output from the photoelectric conversion element arrays. For example, a pair of light beams that have passed through different areas of the exit pupil plane of the photographing optical system are received by an image sensor, a pair of light images formed on the image sensor are converted into a pair of electrical signal data strings, and A focus detection device that detects the focus adjustment state of a photographing optical system by calculating the correlation of a signal data string is known (see, for example, Patent Document 1).

Prior art documents related to the invention of this application include the following.
JP 04-338905 A

  However, in the above-described conventional correlation calculation method, a pair of signal data sequences A1, A2,..., AN and B1, B2,..., BN (N is the number of data) are compared while changing the shift amount k. Since the sum Σ | An−Bn + k | of the absolute values of the differences between the two signal data sequences is simply obtained and used as the correlation amount C (k) between the two signal data sequences, for example, one of the pair of light fluxes has a photographing optical system. When the “vignetting” occurs due to the relative distortion of the pair of signal data strings output from the image sensor, the correlation between the two signal data strings cannot be accurately detected.

According to a first aspect of the present invention, a correlation calculation apparatus photoelectrically converts an image of a light beam that has passed through an imaging optical system, and outputs a first electric signal data string in which a plurality of electric signal data are sequentially arranged. Photoelectric conversion means, second photoelectric conversion means for photoelectrically converting an image of a light beam that has passed through the imaging optical system, and outputting a second electric signal data sequence in which a plurality of electric signal data are sequentially arranged; as the first electrical signal data string a first target electrical signal data first electrical signal data in the interest of the first electrical signal data and in the first electrical signal data string, the target of the first electrical signal data First calculation data and second calculation data are respectively calculated by performing first calculation and second calculation on at least one first nearby electric signal data in the vicinity, and the first calculation data is calculated as the second calculation data. Divide by calculation data Third calculating operation data Te, the attention of the first electrical signal data by sequentially shifting the first in an electric signal data train, a first arithmetic means for generating a third operation data sequence, said second electrical signal data string Among the second electrical signal data corresponding to the first electrical signal data of interest and at least one second nearby electrical signal data in the vicinity of the second electrical signal data in the second electrical signal data string. The fourth calculation data and the fifth calculation data are calculated by performing the first calculation and the second calculation, respectively, and the fourth calculation data is divided by the fifth calculation data to obtain the sixth calculation data. Second calculation means for calculating and generating a sixth calculation data string by sequentially shifting the second electric signal in response to the shift of the attention first electric signal data ; the third calculation data string; and the sixth relatively the operation data sequence The correlation between the sixth arithmetic data string and the third arithmetic data string while Rashi, as a correlation degree between the first electrical signal data string and the second electrical signal data string, and the correlation calculating means for calculating, And the first calculation includes at least the target first electric signal data, wherein the first calculation data that is the first calculation result for the target first electric signal data and the first neighboring electric signal data includes: The fourth calculation data that is the first calculation result for the second electric signal data and the second neighboring electric signal data is an operation that includes at least the second electric signal data, and the second calculation is The second calculation data that is the second calculation result for the attention first electric signal data and the first neighboring electric signal data includes at least the first neighboring electric signal data, The fifth calculation data, which is the second calculation result for the second electric signal data and the second neighboring electric signal data, is a calculation that includes at least the second neighboring electric signal data .
According to a ninth aspect of the present invention, there is provided a correlation calculation device that photoelectrically converts an image of a light beam that has passed through an imaging optical system, and outputs a first electric signal data string in which a plurality of electric signal data are sequentially arranged. Photoelectric conversion means, second photoelectric conversion means for photoelectrically converting an image of a light beam that has passed through the imaging optical system, and outputting a second electric signal data sequence in which a plurality of electric signal data are sequentially arranged; as the first electrical signal data string a first target electrical signal data first electrical signal data in the interest of the first electrical signal data and in the first electrical signal data string, the target of the first electrical signal data First calculation data is calculated by performing a first calculation on at least one first neighboring electric signal data in the vicinity, and corresponds to the first electric signal data of interest in the second electric signal data string Second Telegraph Data and the second in an electric signal data train, and calculating a second operation data by performing the first operation on at least one second vicinity electrical signal data of the vicinity of the second electrical signal data, the The first calculation data is divided by the second calculation data to calculate third calculation data, and the first electric signal data of interest and the second electric signal data are respectively included in the first electric signal data string and the second electric signal. First calculation means for generating a third calculation data sequence by sequentially shifting in the sequence; and the first electric signal data of interest and the first neighboring electric signal data in the first electric signal data sequence The second operation is performed to calculate the fourth operation data, and the second operation is performed on the second electric signal data and the second neighboring electric signal data in the second electric signal data string to obtain the fifth operation data. Calculate the calculation data Said fourth operation data to calculate a sixth operation data by dividing the fifth operation data, the noted first electrical signal data and the second electrical signal data a first electrical signal data string and in the second electric respectively Second calculation means for generating a sixth calculation data string by sequentially shifting in the signal string; and the third calculation data string and the third calculation data string while relatively shifting the third calculation data string and the sixth calculation data string. Correlation degree computing means for computing the degree of correlation with the sixth computation data sequence as the degree of correlation between the first electrical signal data sequence and the second electrical signal data sequence , The first calculation data that is the first calculation result for the first electric signal data of interest and the first neighboring electric signal data includes at least the first electric signal data of interest, and the second electric signal data and the second electric signal data Near electrical signal The second calculation data, which is the first calculation result for the data, includes at least the second electric signal data, and the second calculation includes the first electric signal data of interest and the first electric signal data. The fourth calculation data, which is the second calculation result for the neighboring electric signal data, includes at least the first neighboring electric signal data, and the second calculation for the second electric signal data and the second neighboring electric signal data. The fifth operation data as a result is an operation that includes at least the second neighboring electric signal data .
According to a fifteenth aspect of the present invention, a focus detection apparatus receives a pair of light beams that have passed through a pair of pupil regions of a photographing optical system, and outputs first and second electric signal data strings each composed of a plurality of electric signals. The first electric signal data in the first electric signal data string , the first electric signal data in the first electric signal data string, and the first electric signal data in the first electric signal data string. a first arithmetic data a second operation data calculated respectively by applying focused first operation on at least one of the first neighboring electric signal data of the first near the electrical signal data and the second operation, respectively, said first The third calculation data is generated by dividing the first calculation data by the second calculation data to calculate the third calculation data, and sequentially shifting the attention first electric signal data in the first electric signal data string . 1 calculation means , In the second electrical signal data string, the second in an electric signal data and the second electrical signal data string corresponding to the target first electrical signal data, at least one of the vicinity of the second electrical signal data a The first calculation and the second calculation are respectively performed on two neighboring electric signal data to calculate fourth calculation data and fifth calculation data, respectively, and the fourth calculation data is converted into the fifth calculation data. And second calculation means for generating a sixth calculation data sequence by calculating the sixth calculation data by dividing the second electric signal sequentially in response to the shift of the first electric signal data of interest . 3 operation data string and the sixth operation data string and relatively shifting while the third arithmetic data sequence the correlation between the sixth arithmetic data string, said first electrical signal data string and said second electrical signal The correlation with the data string A correlation degree calculation means for calculating, based on the correlation computed by said correlation computing means, and a focus detection means for detecting a focusing state of the photographing optical system, the first calculation, the interest The first calculation data that is the first calculation result for the first electric signal data and the first neighboring electric signal data includes at least the attention first electric signal data, and the second electric signal data and the second vicinity The fourth calculation data, which is the first calculation result for the electric signal data, is an operation that includes at least the second electric signal data, and the second calculation includes the first electric signal data of interest and the first electric signal data. The second calculation data that is the second calculation result for one neighboring electric signal data includes at least the first neighboring electric signal data, and the second electric signal data and the second electric signal data The fifth calculation data, which is the second calculation result with respect to two neighboring electric signal data, is a calculation that includes at least the second neighboring electric signal data .
According to a sixteenth aspect of the present invention, a focus detection apparatus receives a pair of light beams that have passed through a pair of pupil regions of a photographing optical system, and outputs first and second electric signal data strings each composed of a plurality of electric signals. The first electric signal data in the first electric signal data string , the first electric signal data in the first electric signal data string, and the first electric signal data in the first electric signal data string. It calculates a first calculation data by performing a first operation on at least one of the first neighboring electric signal data near the target first electrical signal data, in the second electrical signal data string, the noted first of the second electrical signal data and the second in an electric signal data string corresponding to the first electrical signal data, the first operation on at least one second vicinity electrical signal data of the vicinity of the second electrical signal data And second calculating the operation data, said first operation data divided by the second operation data to calculate a third operation data, first the attention first electrical signal data and the second electrical signal data, respectively A first calculation means for generating a third calculation data string by sequentially shifting in one electric signal data string and the second electric signal string ; the first electric signal data of interest in the first electric signal data string; The second calculation is performed on the first neighboring electric signal data to calculate the fourth calculation data, and the second electric signal data and the second neighboring electric signal data in the second electric signal data string are calculated. On the other hand, the second calculation is performed to calculate fifth calculation data, the fourth calculation data is divided by the fifth calculation data to calculate sixth calculation data, and the first electric signal data of interest and the first 2Electric signal data Sequentially shifting the first electric signal data string and in the second in an electric signal sequence, relative to the second computing means for generating a sixth operation data sequence, and the third arithmetic data string and the sixth arithmetic data sequence Correlation degree calculating means for calculating the degree of correlation between the third calculation data string and the sixth calculation data string as the degree of correlation between the first electric signal data string and the second electric signal data string Focus detection means for detecting a focus adjustment state of the photographing optical system based on the correlation degree calculated by the correlation degree calculation means, wherein the first calculation includes the first electric signal data of interest and the first The first calculation data, which is the first calculation result for one neighboring electric signal data, includes at least the first electric signal data of interest, and the first for the second electric signal data and the second neighboring electric signal data. Performance The second operation data as a result is an operation that includes at least the second electric signal data, and the second operation is the first operation on the attention first electric signal data and the first neighboring electric signal data. The fifth calculation data which is the second calculation result for the second electric signal data and the second vicinity electric signal data, wherein the fourth calculation data which is two calculation results includes at least the first vicinity electric signal data. Is an operation that includes at least the second neighboring electric signal data .

  According to the present invention, even if, for example, vignetting due to the photographing optical system occurs in one of the pair of focus detection light beams and relative distortion occurs in the pair of signal data strings output from the image sensor, both It is possible to accurately detect the correlation of the signal data sequence.

  An embodiment in which the present invention is applied to a digital still camera as an imaging apparatus will be described. FIG. 1 is a diagram illustrating a configuration of a digital still camera according to an embodiment. A digital still camera 201 according to an embodiment includes an interchangeable lens 202 and a camera body 203, and the interchangeable lens 202 is attached to a mount portion 204 of the camera body 203.

  The interchangeable lens 202 includes lenses 205 to 207, a diaphragm 208, a lens drive control device 209, and the like. The lens 206 is for zooming, and the lens 207 is for focusing. The lens drive control device 209 includes a CPU and its peripheral components, and controls the driving of the focusing lens 207 and the aperture 208, detects the positions of the zooming lens 206, the focusing lens 207 and the aperture 208, and communicates with the control device of the camera body 203. Transmit lens information and receive camera information.

  On the other hand, the camera body 203 includes an image sensor 211, a camera drive control device 212, a memory card 213, an LCD driver 214, an LCD 215, an eyepiece 216, and the like. The imaging element 211 is disposed on the planned image plane (planned focal plane) of the interchangeable lens 202, captures the subject image formed by the interchangeable lens 202, and outputs an image signal. An imaging pixel (hereinafter simply referred to as an imaging pixel) is two-dimensionally arranged in the imaging element 211, and a focus detection pixel (hereinafter, referred to as a focus detection position) is replaced with an imaging pixel in a portion corresponding to the focus detection position. A column (simply called focus detection pixels) is incorporated.

  The camera drive control device 212 includes peripheral components such as a CPU and a memory, and controls the drive of the image sensor 211, processing of the captured image, focus detection and focus adjustment of the interchangeable lens 202, control of the aperture 208, display control of the LCD 215, lens drive Communication with the control device 209, sequence control of the entire camera, and the like are performed. The camera drive control device 212 communicates with the lens drive control device 209 via an electrical contact 217 provided on the mount unit 204.

  The memory card 213 is an image storage that stores captured images. The LCD 215 is used as a display of a liquid crystal viewfinder (EVF: electronic viewfinder), and a photographer can visually recognize a captured image displayed on the LCD 215 via an eyepiece lens 216.

  The subject image that has passed through the interchangeable lens 202 and formed on the image sensor 211 is photoelectrically converted by the image sensor 211, and the image output is sent to the camera drive controller 212. The camera drive control device 212 calculates the defocus amount at the focus detection position based on the output of the focus detection pixel, and sends this defocus amount to the lens drive control device 209. Further, the camera drive control device 212 sends an image signal generated based on the output of the imaging pixel to the LCD driver 214, displays it on the LCD 215, and stores it in the memory card 213.

  The lens drive control device 209 detects the positions of the zooming lens 206, the focusing lens 207, and the diaphragm 208 and calculates lens information based on the detected positions, or a lens corresponding to the detected position from a lookup table prepared in advance. Information is selected and sent to the camera drive controller 212. Further, the lens drive control device 209 calculates the lens drive amount based on the defocus amount received from the camera drive control device 212, and drives and controls the focusing lens 207 based on the lens drive amount.

  FIG. 2 shows a focus detection area on the imaging screen G set on the planned imaging plane of the interchangeable lens 202. The focus detection areas G1 to G5 are set on the imaging screen G, and the focus detection pixels of the imaging element 211 are linearly arranged in the longitudinal direction of the focus detection areas G1 to G5 on the imaging screen G. That is, the focus detection pixel array on the image sensor 211 samples the images of the focus detection areas G1 to G5 in the subject image formed on the shooting screen G. The photographer manually selects an arbitrary focus detection area from the focus detection areas G1 to G5 according to the shooting composition.

  FIG. 3 is a front view showing a detailed configuration of the image sensor 211. FIG. 3 is a partially enlarged view in which the periphery of one focus detection region on the image sensor 211 is enlarged. The image pickup device 211 includes an image pickup pixel 310 and a focus detection pixel 311 for focus detection.

  As shown in FIG. 4, the imaging pixel 310 includes the microlens 10, the photoelectric conversion unit 11, and a color filter (not shown). As shown in FIG. 5, the focus detection pixel 311 includes a microlens 10 and a pair of photoelectric conversion units 12 and 13. The photoelectric conversion unit 11 of the imaging pixel 310 is designed in such a shape that the microlens 10 receives all the light beams that pass through the exit pupil (for example, F1.0) of a bright interchangeable lens. On the other hand, the pair of photoelectric conversion units 12 and 13 of the focus detection pixel 311 are designed so as to receive all light beams passing through a specific exit pupil (for example, F2.8) of the interchangeable lens by the microlens 10.

  The imaging pixels 310 arranged two-dimensionally are provided with red (R), green (G), or blue (B) color filters, and each color filter has the spectral sensitivity characteristics shown in FIG. Yes. The imaging pixels 310 having RGB color filters are arranged in a Bayer array as shown in FIG.

  On the other hand, the focus detection pixel 311 is not provided with a color filter in order to increase the amount of light, and the spectral sensitivity characteristics thereof are the spectral sensitivity of a photodiode that performs photoelectric conversion and the spectral sensitivity of an infrared cut filter (not shown). The spectral sensitivity characteristics shown in FIG. The spectral sensitivity of the focus detection pixel 311 has a spectral sensitivity characteristic that is obtained by adding the spectral sensitivities of the green pixel G, the red pixel R, and the blue pixel B in the imaging pixel 310 shown in FIG. The light wavelength region of the sensitivity of the green pixel G, the red pixel R, and the blue pixel B is included.

  The focus detection pixels 311 are arranged densely in a straight line without a gap in the rows or columns where the B filters and G filters of the imaging pixels 310 in the focus detection regions G1 to G5 shown in FIG. When the focus detection pixel 311 is arranged in a row or a column where the B filter and the G filter of the imaging pixel 310 should be arranged, an error occurs when the pixel signal at the position of the focus detection pixel 311 is calculated by pixel interpolation. But it can be inconspicuous to human eyes. This is because the human eye is more sensitive to red than blue and because the density of green pixels is higher than that of blue and red pixels, the contribution to image degradation for a single pixel defect in the green pixel is small. .

  Note that, in the above-described imaging element in which the imaging pixels of the complementary color filter are developed two-dimensionally, the focus detection pixels 311 are arranged at pixel positions where cyan and magenta including a blue component whose output error is relatively inconspicuous should be arranged.

  FIG. 8 is a cross-sectional view of the imaging pixel 310. In the imaging pixel 310, the microlens 10 is disposed in front of the photoelectric conversion unit 11 for imaging, and the photoelectric conversion unit 11 is projected forward by the microlens 10. The photoelectric conversion unit 11 is formed on the semiconductor circuit substrate 29, and a color filter (not shown) is disposed between the microlens 10 and the photoelectric conversion unit 11.

  FIG. 9 is a cross-sectional view of the focus detection pixel 311. In the focus detection pixel 311, the microlens 10 is disposed in front of the focus detection photoelectric conversion units 12 and 13, and the photoelectric conversion units 12 and 13 are projected forward by the microlens 10. The photoelectric conversion units 12 and 13 are formed on the semiconductor circuit substrate 29.

  Next, a focus detection method based on the pupil division method will be described with reference to FIG. In FIG. 10, the microlens 50 of the focus detection pixel 311 disposed on the optical axis 91 of the interchangeable lens 202, the pair of photoelectric conversion units 52 and 53 disposed behind the microlens 50, and the interchangeable lens 202. The microlens 60 of the focus detection pixel 311 disposed outside the optical axis 91 and the pair of photoelectric conversion units 62 and 63 disposed behind the microlens 60 will be described as an example. The exit pupil 90 of the interchangeable lens 202 is set at a position of a distance d4 in front of the microlenses 50 and 60 arranged on the planned image formation surface of the interchangeable lens 202. Here, the distance d4 is a value determined according to the curvature and refractive index of the microlenses 50 and 60, the distance between the microlenses 50 and 60 and the photoelectric conversion units 52, 53, 62, and 63, and the like. In the specification, this is called a distance measuring pupil distance.

  The microlenses 50 and 60 are arranged on the planned imaging plane of the interchangeable lens 202, and the shape of the pair of photoelectric conversion units 52 and 53 is separated from the microlens 50 by the projection distance d4 by the microlens 50 on the optical axis 91. The projected image is projected onto the exit pupil 90, and the projection shape forms distance measuring pupils 92 and 93. On the other hand, the shape of the pair of photoelectric conversion units 62 and 63 is projected onto the exit pupil 90 separated by the projection distance d4 by the microlens 60 outside the optical axis 91, and the projection shape forms distance measuring pupils 92 and 93. That is, the projection direction of each pixel is determined so that the projection shapes (ranging pupils 92 and 93) of the photoelectric conversion units of the focus detection pixels coincide on the exit pupil 90 at the projection distance d4.

  The photoelectric conversion unit 52 outputs a signal corresponding to the intensity of the image formed on the microlens 50 by the focus detection light beam 72 passing through the distance measuring pupil 92 and traveling toward the microlens 50. The photoelectric conversion unit 53 outputs a signal corresponding to the intensity of the image formed on the microlens 50 by the focus detection light beam 73 passing through the distance measuring pupil 93 and traveling toward the microlens 50. The photoelectric conversion unit 62 outputs a signal corresponding to the intensity of the image formed on the microlens 60 by the focus detection light beam 82 passing through the distance measuring pupil 92 and traveling toward the microlens 60. The photoelectric conversion unit 63 outputs a signal corresponding to the intensity of the image formed on the microlens 60 by the focus detection light beam 83 passing through the distance measuring pupil 93 and traveling toward the microlens 60. Note that the arrangement direction of the focus detection pixels 311 is made to coincide with the division direction of the pair of pupil distances.

  A large number of such focus detection pixels are arranged in a straight line, and the output of the pair of photoelectric conversion units of each pixel is collected into an output group corresponding to the distance measurement pupil 92 and the distance measurement pupil 93, thereby forming a pair of distance measurement pupils 92. And 93, information relating to the intensity distribution of a pair of images formed on the focus detection pixel column by the focus detection light fluxes passing through each of them can be obtained. Furthermore, by applying an image shift detection calculation process (correlation process, phase difference detection process) to be described later to this information, the image shift amount of a pair of images can be detected by a so-called pupil division method. Then, by multiplying this image shift amount by a predetermined conversion coefficient, the current imaging plane (imaging plane at the focus detection position corresponding to the position of the microlens array on the planned imaging plane) with respect to the planned imaging plane is determined. Deviation (defocus amount) can be calculated.

  In FIG. 10, the first focus detection pixel (the microlens 60 and the pair of photoelectric conversion units 62) adjacent to the first focus detection pixel (the microlens 50 and the pair of photoelectric conversion units 52 and 53) on the optical axis 91. 63) is also schematically illustrated, but in other focus detection pixels as well, similarly, a pair of photoelectric conversion units receive light beams coming from the pair of distance measuring pupils to the respective microlenses.

  FIG. 11 is a front view showing a projection relationship on the exit pupil plane. The circumscribed circle of the distance measuring pupils 92 and 93 obtained by projecting the pair of photoelectric conversion units 12 and 13 from the focus detection pixel 311 onto the exit pupil plane 90 by the microlens 10 is a predetermined aperture F value (when viewed from the imaging plane). Hereinafter, it is referred to as a distance measuring pupil F value, which is F2.8). When the photoelectric conversion unit 11 of the imaging pixel 310 is projected onto the exit pupil plane 90 by the microlens 10, the region 94 is formed, and the region 94 is a wide region including the distance measuring pupils 92 and 93.

  In FIG. 11, the positional relationship between the center of the region 95 corresponding to the aperture opening of the interchangeable lens 202 indicated by the broken line and the center of the circumscribed circle of the distance measuring pupils 92 and 93 is the position and focal point of the exit pupil unique to the interchangeable lens 202. The detection pixel changes according to the position on the screen (distance from the optical axis) and does not necessarily match. When the size of the exit pupil of the interchangeable lens 202 is smaller than the size of the circumscribed circle of the distance measuring pupils 92 and 93 and the centers do not coincide with each other, the light beams passing through the pair of distance measuring pupils 92 and 93 are unbalanced. “Vignetting” occurs, and the amount of light of the pair of images formed by these light beams does not match, resulting in distortion.

  FIG. 12 shows the intensity distribution (light quantity) of the image signal at one focus detection position on the vertical axis and the position deviation within the focus detection position on the horizontal axis. The position deviation within the focus detection position corresponds to the positions of a plurality of focus detection pixels belonging to one focus detection position on the image sensor 211 shown in FIG. 3, for example. In the pair of image signals 400 and 401 when no vignetting occurs in the focus detection light beam, the same image signal function is simply shifted horizontally as shown in FIG. When vignetting occurs in the focus detection light beam, the amount of the focus detection light beam passing through the distance measuring pupil changes depending on the focus detection position and the position deviation within the focus detection position, and the pair of image signals 402 and 403 are shown in FIG. Thus, the same signal is not relatively shifted.

《Imaging operation》
FIG. 13 is a flowchart illustrating an imaging operation of the digital still camera (imaging device) 210 according to the embodiment. The camera drive control device 212 repeatedly executes this imaging operation when the camera is turned on in step 100. In step 110, the data of the imaging pixel 310 is read out from the imaging device 211 and displayed on the electronic viewfinder LCD 215. When the data of the imaging pixel 310 is thinned and read out, the display quality can be improved by performing the thinning out reading with a setting that does not include the focus detection pixel 311 as much as possible. Conversely, by performing thinning readout so as to include the focus detection pixel 311 and displaying it on the electronic viewfinder LCD 215 without correcting the focus detection pixel output, the focus detection position can be displayed recognizable to the user. .

  In step 120, data is read from the focus detection pixel array. Since an arbitrary area is selected in advance from the focus detection areas G1 to G5 shown in FIG. 2 by an area selection operation member (not shown), data is acquired from the focus detection pixel row corresponding to the selected focus detection area. Is read. In subsequent step 130, based on a pair of image data corresponding to the focus detection pixel row, an image shift detection calculation process, that is, a correlation calculation process, which will be described later, is performed to calculate the image shift amount, and further calculate the defocus amount. In step 140, it is checked whether or not the focus is close, that is, whether or not the calculated absolute value of the defocus amount is within the focus determination reference value.

  If it is determined that the lens is not in focus, the process proceeds to step 150, the calculated defocus amount is transmitted to the lens drive control device 209, the focusing lens 207 of the interchangeable lens 202 is driven to the focus position, and the process returns to step 110. Repeat the above operation. Even when focus detection is impossible, the process branches to step 150, a scan drive command is transmitted to the lens drive control device 209, and the focusing lens 207 of the interchangeable lens 202 is driven to scan between the infinite position and the closest position. Returning to 110, the above operation is repeated.

  On the other hand, if it is determined that it is close to the in-focus state, the process proceeds to step 160 to determine whether or not a shutter release has been performed by operating a release button (not shown). If not, the process returns to step 110 to perform the above operation. repeat. When the shutter release is performed, the process proceeds to step 170, an aperture adjustment command is transmitted to the lens drive control device 209, and the control F value determined by the exposure calculation of the aperture 208 of the interchangeable lens 202 by the camera drive control device 212, or the user Set the manually set F value.

  When the aperture control is completed, the image sensor 211 is caused to perform an imaging operation, and image data is read from the image pickup pixel 310 and all the focus detection pixels 311 of the image pickup element 211. In step 180, pixel data at each pixel position in the focus detection pixel row is interpolated based on the data of the focus detection pixel 311 and the data of the surrounding imaging pixels 310. In step 190, image data composed of the data of the imaging pixel 310 and the interpolated focus detection pixel position data is stored in the memory card 213, and the process returns to step 110 to repeat the above operation.

<Focus detection operation>
FIG. 14 is a flowchart showing details of the focus detection operation in step 130 in the imaging operation shown in FIG. In step 200, focus detection calculation processing, that is, correlation calculation processing is started. In step 210, a pair of signal data sequences (α1 to αM, β1 to βM: M is the number of data) are output as follows. High frequency cut filter processing as shown in equation (1) is performed to generate first signal data strings A1 to AN and second signal data strings B1 to BN (N is the number of data), and adversely affect correlation processing from the signal data strings. Remove noise components and high frequency components.
An = αn + 2 × αn + 1 + αn + 2,
Bn = βn + 2 × βn + 1 + βn + 2 (1)
In the formula (1), n = 1 to N. Note that the high-frequency cut filter processing in step 210 can be omitted when the calculation time is to be shortened or when it is known that the high-frequency component is small because the focus has already been greatly defocused.

  In step 220, the first calculation data is obtained by performing a first calculation on at least one of data of interest (hereinafter simply referred to as data of interest) An in the first signal data string A1 to AN and data in the vicinity thereof. At the same time, the second calculation data is generated by performing the second calculation. Then, the first calculation data is divided by the second calculation data to generate third calculation data En related to the first signal data strings A1 to AN. The first calculation and the second calculation will be described later. Further, the third calculation data En is accumulated while shifting the attention data An in the first signal data strings A1 to AN to generate the third calculation data strings E1 to EL. The third calculation data string E1 to EL has a gain in the data of interest An and the data range An-r to An + s in the vicinity thereof (r and s are arbitrary integers; hereinafter, this range is referred to as a “small range”). Is a standardized data string.

  Next, in step 230, data Bn + k (k is a shift amount of a pair of data strings (details will be described later) in the second signal data strings B1 to BN corresponding to the data of interest An in the first signal data string). ) And its neighboring data, the first calculation is performed to generate the fourth calculation data, and the second calculation is performed to generate the fifth calculation data. Then, the fourth calculation data is divided by the fifth calculation data to generate a sixth calculation data string Fn related to the second signal data strings B1 to BN. Note that the first calculation and the second calculation are the same as the first calculation and the second calculation in step 220, and will be described later. Further, the sixth operation data Fn is accumulated while shifting the data of interest Bn + k in the second signal data sequences B1 to BN to generate sixth operation data sequences F1 to FL. The sixth operation data F1 to FL are the data of interest Bn + k and the data range in the vicinity thereof Bn-r + k to Bn + s + k (r and s are arbitrary integers; In this case, the gain is a standardized data string.

In step 240, the third calculation data string E1 to EL related to the first signal data string A1 to AN and the sixth calculation data string F1 to FL related to the second data string B1 to BN are shifted relative to each other by k. To calculate the correlation amount C (k).
C (k) = Σ | En−Fn + k | (2)
In equation (2), the range taken by n in the Σ operation is limited to the range where En and Fn + k data exist according to the shift amount k. The shift amount k between the pair of data strings E1 to EL and F1 to FL is an integer, and is a relative shift amount with the detection pitch of the pair of data strings as a unit.

In step 250, as shown in FIG. 15 (a), for example, as shown in FIG. 15 (a), the correlation amount C (k) is the minimum (the smaller the shift amount k = kj = 2), the higher the correlation between the pair of data. Correlation degree is high). A shift amount x that gives a minimum value C (x) with respect to a continuous correlation amount is obtained using a three-point interpolation method according to the following equations (3) to (6).
x = kj + D / SLOP (3),
C (x) = C (kj) − | D | (4),
D = {C (kj-1) -C (kj + 1)} / 2 (5),
SLOP = MAX {C (kj + 1) -C (kj), C (kj-1) -C (kj)} (6)

In step 260, the defocus amount DEF of the subject image plane with respect to the planned image formation plane can be obtained by the following equation (7) based on the shift amount x obtained by the equation (3).
DEF = KX · PY · x (7)
In equation (7), PY is a detection pitch, and KX is a conversion coefficient determined by the size of the opening angle of the center of gravity of the pair of distance measuring pupils. Whether or not the calculated defocus amount DEF is reliable is determined as follows. As shown in FIG. 15B, when the correlation between the pair of data is low, the value of the interpolated minimum amount C (x) of the correlation amount becomes large. Therefore, when C (x) is equal to or greater than a predetermined value, it is determined that the reliability is low. Alternatively, in order to normalize C (x) with the contrast of data, if the value obtained by dividing C (x) by SLOP that is proportional to the contrast is equal to or greater than a predetermined value, it is determined that the reliability is low. Alternatively, when SLOP that is a value proportional to the contrast is equal to or less than a predetermined value, it is assumed that the subject has low contrast and the reliability of the calculated defocus amount DEF is low.

  In step 270, the focus detection calculation process, that is, the correlation calculation process ends, and the process returns.

《Correlation operation》
Next, an example of the correlation calculation process shown in FIG. 14 will be described. FIG. 16 is a diagram for explaining the concept of correlation calculation according to an embodiment. The interchangeable lens 202 is divided into first signal data strings A1 to AN indicated by solid lines and second signal data strings B1 to BN indicated by broken lines. A case where distortion caused by vignetting or the like occurs and a gain difference occurs between the waveforms of both signal data strings is shown. Even when there is such a gain difference, the “small range” characteristics in each signal data string, that is, the ratio of the sizes of adjacent data is not greatly affected. The degree of correlation (similarity) between B1 to BN can be detected with high accuracy. Furthermore, by accumulating the degree of correlation while shifting the “small range” within a predetermined range, it is possible to eliminate the accidental degree of correlation and perform more accurate correlation detection.

In this embodiment, the first calculation is performed on at least one of the data of interest An in the first signal data string A1 to AN and the data in the vicinity thereof to generate the first calculation data, and the second An operation is performed to generate second operation data. Then, the first calculation data is divided by the second calculation data to generate third calculation data strings E1 to EL related to the first signal data strings A1 to AN.
Further, the first calculation is performed on at least one of the data Bn + k in the second signal data string B1 to BN corresponding to the position of the target data An in the first signal data string and the data in the vicinity thereof. The fourth calculation data is generated, and the second calculation is performed to generate the fifth calculation data. Then, the fourth calculation data is divided by the fifth calculation data to generate sixth calculation data strings F1 to FL related to the second signal data strings B1 to BN.
Then, the correlation between the first signal data string A1 to AN and the second signal data string B1 to BN is obtained by the above equation (2) based on the third calculation data string E1 to EL and the sixth calculation data string F1 to FL. Hereinafter, this correlation calculation processing example will be described.

<< Correlation calculation processing example 1 >>
The correlation amount (k) is obtained by the following equation.
C (k) = Σ | (An / An + 1) − (Bn + k / Bn + 1 + k) | (8)
In equation (8), the Σ operation is accumulated for n, and the range taken by n is limited to a range in which data of An, An + 1, Bn + k, and Bn + 1 + k exist according to the shift amount k. . FIG. 17 shows a data flow of correlation calculation processing example 1.

  In this correlation calculation processing example 1, attention data An in the first signal data string A is set as first calculation data, and neighboring data An + 1 of the attention data An is set as second calculation data. Then, the first calculation data An is divided by the second calculation data An + 1 to generate a third calculation data string (An / An + 1) related to the first signal data strings A1 to AN. Further, the data Bn + k in the second signal data string B corresponding to the attention data An in the first signal data string is set as the fourth operation data, and the neighboring data Bn + 1 + k of the data Bn + k is set as the fifth data. Calculated data. Then, the fourth operation data Bn + k is divided by the fifth operation data Bn + 1 + k, and a sixth operation data sequence (Bn + k / Bn + 1 + k) related to the second signal data sequences B1 to BN is obtained. Is generated. Then, the correlation amount C (k) between the first signal data string A and the second signal data string B is calculated based on the sum of absolute values of the differences between the third calculation data and the sixth calculation data. In this correlation calculation processing example 1, both the first calculation and the second calculation described above are calculated as (calculation target data × 1), and substantially no calculation is performed.

  Here, a case where the correlation calculation processing example 1 is performed on a pair of image signal data strings A and B as shown in FIG. 18 will be considered. A relative distortion occurs in a pair of image signal data strings (A1, A2,..., AN), (B1, B2,..., BN) output from the image sensor 211, and as shown in FIG. It is assumed that there is a difference between the gain and inclination of the waveform (1 + sinω) of both image signal data strings. FIG. 19 shows the result of executing the correlation calculation processing example 1 on these two signal data strings A and B. As is clear from the figure, it can be seen that, even though the two signal data strings A and B are distorted, the correlation calculation processing example 1 can obtain a high correlation (a depressed position) periodically.

  According to this correlation calculation processing example 1, the above-described conventional correlation calculation method, that is, simply obtaining the sum Σ | An−Bn + k | of the absolute values of the differences between the two signal data strings A and B is used to Compared with the correlation amount C (k), the correlation amount between the two signal data strings A and B can be accurately obtained even when relative distortion occurs in the two signal data strings A and B. it can. Further, in this correlation calculation processing example 1, since the denominator of the correlation calculation formula (8) does not include multiplication / division of data, the probability of calculation divergence due to the denominator being zero is reduced. Furthermore, since the numerator does not include multiplication / division of data, the time required for correlation calculation is shortened.

<< Correlation calculation processing example 2 >>
The correlation amount C (k) is obtained by the following equation.
C (k) = Σ {| (An / An + 1) − (Bn + k / Bn + 1 + k) | × MIN (An + 1, Bn + 1 + k)}
... (9)
In equation (9), the Σ operation is accumulated for n, and the range taken by n is limited to a range in which data of An, An + 1, Bn + k, and Bn + 1 + k exist according to the shift amount k. . MIN () is a function for selecting the minimum value of data from a plurality of data. FIG. 20 shows a data flow of the correlation calculation processing example 1.

  Expression (9) in this correlation calculation processing example 2 is an arithmetic expression that weights the above-described expression (8) in correlation calculation processing example 1 with the minimum value of the denominator in the expression (8). In this correlation calculation processing example 2, both the first calculation and the second calculation described above are calculated as (calculation target data × 1), and substantially no calculation is performed.

  FIG. 21 shows the result of executing the correlation calculation process 2 on the signal data strings A and B shown in FIG. 18 in which relative distortion has occurred in the two signal data strings A and B. As is apparent from the figure, it can be seen that, even though the two signal data strings A and B are distorted, the correlation calculation processing example 2 can provide a high correlation (a depressed position) periodically. According to the correlation calculation processing example 2, in addition to the effect of the correlation calculation processing example 1 described above, when the value of the denominator is small, the value of the equation (8) fluctuates due to the noise component included in the data, thereby detecting the correlation. Decrease in accuracy can be prevented, and noise resistance can be improved.

<< Correlation calculation processing example 3 >>
The correlation amount C (k) is obtained by the following equation.
C (k) = Σ | An / (An + An + 1) -Bn + k / (Bn + k + Bn + 1 + k) | (10)
In equation (10), the Σ operation is accumulated for n, and the range taken by n is limited to a range in which data of An, An + 1, Bn + k, and Bn + 1 + k exist according to the shift amount k. . FIG. 22 shows a data flow of the correlation calculation processing example 3.

  The correlation calculation formula (10) of this correlation calculation processing example 3 is a calculation formula in which the denominator of the formula (8) is changed to the sum of two data, that is, twice the average value of the two data. In this correlation calculation processing example 3, the first calculation described above is calculated as (calculation target data × 1), and substantially no calculation is performed. On the other hand, the above-described second calculation is an average calculation for adding the attention data An and its neighboring data An + 1 to the first signal data string A, and the attention data Bn for the second signal data string B. An average operation of adding + k (data corresponding to the data of interest An in the first signal data string) and its neighboring data Bn + 1 + k is performed.

  FIG. 23 shows the result of executing correlation calculation processing example 3 on the signal data strings A and B shown in FIG. 18 in which relative distortion has occurred in the two signal data strings A and B. As is clear from the figure, it can be seen that, although the two signal data strings A and B are distorted, the correlation calculation processing example 3 can obtain a high correlation (a depressed position) periodically. According to this correlation calculation processing example 3, in addition to the above-described effects of the correlation calculation processing example 1, it is possible to prevent the noise component included in the denominator portion from being stochastically reduced and to prevent the correlation detection accuracy from being lowered. Can be improved.

<< Correlation calculation processing example 4 >>
The correlation amount C (k) is obtained by the following equation.
C (k) = Σ | (An−An + 1) / (An + An + 1) − (Bn + k−Bn + 1 + k) / (Bn + k + Bn + 1 + k) |
(11)
In equation (11), the Σ operation is accumulated for n, and the range taken by n is limited to a range in which data of An, An + 1, Bn + k, and Bn + 1 + k exist according to the shift amount k. . FIG. 24 shows a data flow of the correlation calculation processing example 4.

  The correlation calculation formula (11) in this correlation calculation processing example 4 is a calculation formula in which the numerator of the formula (10) in the correlation calculation processing example 3 is changed to a difference between two data, that is, a first derivative. In the correlation calculation formula (11) of this correlation calculation processing example 4, the first calculation described above is a first-order differential calculation for subtracting the neighboring data An + 1 from the data of interest An for the first signal data string A. For the second signal data string B, a first-order differential operation is performed by subtracting the neighboring data Bn + 1 + k from the data of interest Bn + k (data corresponding to the data of interest An of the first signal data string). On the other hand, the above-described second calculation is an average calculation for adding the attention data An and its neighboring data An + 1 to the first signal data string A, and the attention data Bn for the second signal data string B. An average operation is performed by adding + k and its neighboring data Bn + 1 + k.

  FIG. 25 shows a result of executing the correlation calculation processing example 4 on the signal data strings A and B shown in FIG. 18 in which relative distortion has occurred in the two signal data strings A and B. As is clear from the figure, it can be seen that, although the two signal data strings A and B are distorted, the correlation calculation processing example 4 can obtain a high correlation (a depressed position) periodically. According to the correlation calculation process 4, in addition to the effects of the correlation calculation process example 1 and the correlation calculation process example 3 described above, the noise component included in the denominator is reduced stochastically, and the correlation detection accuracy is reduced. Can be prevented, and noise resistance can be improved. In addition, the DC component included in the data string can be removed, and even when the two data strings A and B include DC offsets, highly accurate correlation detection is possible, and the DC offset resistance performance is improved.

<< Modification of Correlation Calculation Processing Example 4 >>
The correlation amount C (k) is obtained by the following equation.
C (k) = Σ | (An−An + 2) / (An + An + 2) − (Bn + k−Bn + 2 + k) / (Bn + k + Bn + 2 + k) |
(12)
In equation (12), the Σ operation is accumulated for n, and the range taken by n is limited to the range in which data of An, An + 2, Bn + k, and Bn + 2 + k exist according to the shift amount k. . The correlation calculation formula (12) is a calculation formula in which the interval of calculation target data of the correlation calculation formula (11) is widened, that is, the above-mentioned “small range” is expanded, and the DC offset resistance performance can be changed. it can.

<< Correlation calculation processing example 5 >>
The correlation amount C (k) is obtained by the following equation.
C (k) = Σ | (2 × An−An−1−An + 1) / (An−1 + An + An + 1) − (2 × Bn + k−Bn−1 + k−Bn + 1 + k) / ( Bn-1 + k + Bn + k + Bn + 1 + k) | (13)
In equation (13), the Σ operation is accumulated for n, and the range taken by n is An-1, An, An + 1, Bn-1 + k, Bn + k, Bn + 1 + k according to the shift amount k. It is limited to the range where the data of exists. FIG. 26 shows a data flow of the correlation calculation processing example 5.

  In correlation calculation processing example 5 (13), the numerator portion of the correlation calculation expression (10) is changed to addition / subtraction of three data, that is, a second order differential calculation. In the equation (13) of this correlation calculation processing example 5, the first calculation described above is the second-order differential calculation in the “minor range” of the data of interest of the first signal data string A and the second signal data string B and its neighboring data. The second calculation is an average calculation in the “small range” of the data of interest of the first signal data string A and the second signal data string B and its neighboring data.

  FIG. 27 shows the result of executing the correlation calculation processing 5 on the signal data strings A and B shown in FIG. 18 in which relative distortion has occurred in the two signal data strings A and B. As is clear from the figure, it can be seen that, even though the two signal data strings A and B are distorted, the correlation calculation processing example 5 can obtain a high correlation (a depressed position) periodically. According to the correlation calculation processing 5, in addition to the effects of the correlation calculation processing example 1 and the correlation calculation processing example 4 described above, the noise component included in the denominator is reduced stochastically, and the correlation detection accuracy is reduced. Can be prevented, and noise resistance can be improved. Further, the DC component and the first-order gradient component included in the data string can be removed, and even when the two data strings A and B include a difference in DC offset or first-order gradient component, highly accurate correlation detection is possible. Thus, the DC offset resistance is improved.

<< Modification of Correlation Calculation Processing Example 5 >>
The correlation amount C (k) is obtained by the following equation.
C (k) = Σ | (2 × An−An−2−An + 2) / (An−2 + An + An + 2) − (2 × Bn + k−Bn−2 + k−Bn + 2 + k) / ( Bn-2 + k + Bn + k + Bn + 2 + k) | (14)
In equation (14), the Σ operation is accumulated for n, and the range taken by n is An-2, An, An + 2, Bn-2 + k, Bn + k, Bn + 2 + k according to the shift amount k. It is limited to the range where the data of exists. This correlation calculation formula (14) is a calculation formula in which the interval of calculation target data of the correlation calculation formula (13) is widened, that is, the above-mentioned “small range” is expanded, and the anti-DC offset performance can be changed. it can.

<< Correlation calculation processing example 6 >>
The correlation amount C (k) is obtained by the following equation.
C (k) = Σ {| An ² / (An−1 × An + 1) −Bn + k ² / (Bn−1 + k × Bn + 1 + k) | × MIN (An−1, An + 1) , Bn-1 + k, Bn + 1 + k)} (15)
In equation (15), the Σ operation is accumulated for n, and the range taken by n is An-1, An, An + 1, Bn-1 + k, Bn + k, Bn + 1 + k according to the shift amount k. It is limited to the range where the data of exists. MIN () is a function for selecting the minimum value of data from a plurality of data. FIG. 28 shows a data flow of the correlation calculation processing example 6.

  The calculation formula (15) of the correlation calculation processing example 6 is weighted by the minimum value of the denominator. In the calculation formula (15), the first calculation described above is a calculation of squaring the data of interest of the first signal data string A and the second signal data string B, and the second calculation is the first signal data string A and This is an operation of multiplying neighboring data of the data of interest in the second signal data string B.

  FIG. 29 shows the result of executing the correlation calculation processing example 6 on the signal data strings A and B shown in FIG. 18 in which relative distortion has occurred in the two signal data strings A and B. As is apparent from the figure, it can be seen that, even though the two signal data strings A and B are distorted, the correlation calculation processing example 6 can obtain a high correlation (a depressed position) periodically. According to this correlation calculation processing example 6, in addition to the effect of the correlation calculation processing example 1 described above, weighting is performed by the minimum value of the denominator part, so that when the denominator part value is small, the correlation is caused by the noise component included in the data. It can be prevented that the calculation result fluctuates and the correlation detection accuracy is lowered, and the noise resistance performance is improved.

<< Correlation calculation processing example 7 >>
The correlation amount C (k) is obtained by the following equation.
C (k) = Σ | An 2 / {(An-1 + An) × (An + An + 1)} - Bn + k 2 / {(Bn-1 + k + Bn + k) × (Bn + k + Bn + 1 + k)} | (16)
In equation (16), the Σ operation is accumulated for n, and the range taken by n is An-1, An, An + 1, Bn-1 + k, Bn + k, Bn + 1 + k according to the shift amount k. It is limited to the range where the data of exists. FIG. 30 shows a data flow of the correlation calculation processing example 7.

  In the calculation formula (16) of the correlation calculation processing example 7, the first calculation described above is a calculation to square the attention data of the first signal data string A and the second signal data string B. On the other hand, the second calculation is an operation of multiplying two values obtained by adding the data of interest of the first signal data string A and the second signal data string B and data in the vicinity thereof.

  FIG. 31 shows the result of executing correlation calculation processing example 7 on the signal data strings A and B shown in FIG. 18 in which relative distortion has occurred in the two signal data strings A and B. As is clear from the figure, it can be seen that, even though the two signal data strings A and B are distorted, the correlation calculation processing example 7 provides a high correlation (a depressed position) periodically. According to this correlation calculation processing example 7, in addition to the effects of the correlation calculation processing example 1 described above, the denominator is obtained by adding two data in a very small range near the data of interest in the two signal data strings A and B. By multiplying the two values, the noise component contained in the denominator is stochastically reduced, and it is possible to prevent the correlation detection accuracy from being lowered, and the noise resistance performance is improved.

<< Correlation calculation processing example 8 >>
The correlation amount C (k) is obtained by the following equation.
C (k) = Σ | (An-1−An) × (An−An + 1) / {(An−1 + An) × (An + An + 1)} − (Bn−1 + k−Bn + k) × ( Bn + k−Bn + 1 + k) / {(Bn-1 + k + Bn + k) × (Bn + k + Bn + 1 + k)} |
... (17)
In the equation (17), the Σ operation is accumulated for n, and the range taken by n is An-1, An, An + 1, Bn-1 + k, Bn + k, Bn + 1 + k according to the shift amount k. It is limited to the range where the data of exists. FIG. 32 shows a data flow of the correlation calculation processing example 8.

  The calculation formula (17) of this correlation calculation processing example 8 is obtained by changing the numerator part (first calculation) of the above formula (16), and the first calculation is the data of interest of the two signal data strings A and B. And the neighboring data, that is, an operation of multiplying two values obtained by first-order differentiation, and the second operation is similar to the equation (16), and the data of interest of the two signal data strings A and B and its This is an operation of multiplying two values obtained by adding neighboring data.

  FIG. 33 shows a result of executing the correlation calculation processing example 8 on the signal data strings A and B shown in FIG. 18 in which relative distortion has occurred in the two signal data strings A and B. As is apparent from the figure, it can be seen that, although the two signal data strings A and B are distorted, the correlation calculation processing example 8 can provide a high correlation (a depressed position) periodically. According to the correlation calculation processing example 8, in addition to the effects of the correlation calculation processing example 1 and the correlation calculation processing example 7 described above, the numerator portion is the primary differential calculation of the data of interest and its neighboring data. The DC components included in A and B are removed, and even when the signal data strings A and B include a DC offset, highly accurate correlation detection is possible.

<< Modifications of Correlation Calculation Processing Examples 1 to 8 >>
In the correlation calculation processing examples 1 to 8 described above, an example in which the first calculation and the second calculation are performed on the same signal data string, that is, a ratio between data in a minute range of the same signal data string, for example, An / An + 1, Although an example in which Bn + k / Bn + 1 + k is used for the correlation calculation as the characteristics of the data string has been shown, the ratio between the data in a minute range of different signal data strings, for example, An / Bn + k, An + 1 / Bn The same effect can be obtained even if + 1 + k is used for the correlation calculation as the characteristic of the data string. A modified example in which the following equations (18) to (27) are used instead of the correlation operation equations (8) to (17) used in the correlation operation processing examples 1 to 8 described above will be described.

<< Modification of Correlation Calculation Processing Example 1 >>
Instead of the correlation calculation formula (8) in the correlation calculation processing example 1, the correlation amount C (k) is obtained by the following formula.
C (k) = Σ | An / Bn + k−An + 1 / Bn + 1 + k | (18)
In equation (18), the Σ operation is accumulated for n, and the range taken by n is limited to a range in which data of An, An + 1, Bn + k, and Bn + 1 + k exist according to the shift amount k. .

<< Modification of Correlation Calculation Processing Example 2 >>
Instead of the correlation calculation formula (9) in the correlation calculation processing example 2, the correlation amount C (k) is obtained by the following formula.
C (k) = Σ {| An / Bn + k−An + 1 / Bn + 1 + k | × MIN (Bn + k, Bn + 1 + k)}
... (19)
In equation (19), the Σ operation is accumulated for n, and the range taken by n is limited to a range in which data of An, An + 1, Bn + k, and Bn + 1 + k exist according to the shift amount k. . MIN () is a function for selecting the minimum value of data from a plurality of data.

<< Modification of Correlation Calculation Processing Example 3 >>
Instead of the correlation calculation formula (10) in the correlation calculation processing example 3, the correlation amount C (k) is obtained by the following formula.
C (k) = Σ | An / Bn + k− (An + An + 1) / (Bn + k + Bn + 1 + k) | (20)
In equation (20), the Σ operation is accumulated for n, and the range taken by n is limited to a range in which data of An, An + 1, Bn + k, and Bn + 1 + k exist according to the shift amount k. .

<< Modification of Correlation Calculation Processing Example 4 >>
Instead of the correlation calculation formula (11) in the correlation calculation processing example 4, the correlation amount C (k) is obtained by the following formula.
C (k) = Σ | (An−An + 1) / (Bn + k−Bn + 1 + k) − (An + An + 1) / (Bn + k + Bn + 1 + k) |
... (21)
In equation (21), the Σ operation is accumulated for n, and the range taken by n is limited to a range in which data of An, An + 1, Bn + k, and Bn + 1 + k exist according to the shift amount k. .

Instead of the correlation calculation formula (12) of the modified example of the correlation calculation processing example 4, the correlation amount C (k) is obtained by the following formula.
C (k) = Σ | (An−An + 2) / (Bn + k−Bn + 2 + k) − (An + An + 2) / (Bn + k + Bn + 2 + k) |
(22)
In equation (22), the Σ operation is accumulated for n, and the range taken by n is limited to a range in which data of An, An + 2, Bn + k, and Bn + 2 + k exist according to the shift amount k. .

<< Modification of Correlation Calculation Processing Example 5 >>
Instead of the correlation calculation formula (13) of the correlation calculation processing example 5, the correlation amount C (k) is obtained by the following formula.
C (k) = Σ | (2 × An−An−1−An + 1) / (2 × Bn + k−Bn−1 + k−Bn + 1 + k) − (An−1 + An + An + 1) / ( Bn-1 + k + Bn + k + Bn + 1 + k) | (23)
In equation (23), the Σ operation is accumulated for n, and the range taken by n is An-1, An, An + 1, Bn-1 + k, Bn + k, Bn + 1 + k according to the shift amount k. It is limited to the range where the data of exists.

Instead of the correlation calculation formula (14) in the correlation calculation processing example 5, the correlation amount C (k) is obtained by the following formula.
C (k) = Σ | (2 × An−An−2−An + 2) / (2 × Bn + k−Bn−2 + k−Bn + 2 + k) − (An−2 + An + An + 2) / ( Bn-2 + k + Bn + k + Bn + 2 + k) | (24)
In equation (24), the Σ operation is accumulated for n, and the range taken by n is An-2, An, An + 2, Bn-2 + k, Bn + k, Bn + 2 + k according to the shift amount k. It is limited to the range where the data of exists.

<< Modification of Correlation Calculation Processing Example 6 >>
Instead of the correlation calculation formula (15) of the correlation calculation processing example 6, the correlation amount C (k) is obtained by the following formula.
C (k) = Σ {| An 2 / Bn + k 2 - (An-1 × An + 1) / (Bn-1 + k × Bn + 1 + k) | × MIN (Bn-1 + k, Bn + k, Bn + 1 + k)) (25)
In equation (25), the Σ operation is accumulated for n, and the range taken by n is An-1, An, An + 1, Bn-1 + k, Bn + k, Bn + 1 + k according to the shift amount k. It is limited to the range where the data of exists. MIN () is a function for selecting the minimum value of data from a plurality of data.

<< Modification of Correlation Calculation Processing Example 7 >>
Instead of the correlation calculation formula (16) of the correlation calculation processing example 7, the correlation amount C (k) is obtained by the following formula.
C (k) = Σ | An 2 / Bn + k 2 - {(An-1 + An) × (An + An + 1)} / {(Bn-1 + k + Bn + k) × (Bn + k + Bn + 1 + k)) | (26)
In the equation (26), the Σ operation is accumulated for n, and the range taken by n is An-1, An, An + 1, Bn-1 + k, Bn + k, Bn + 1 + k according to the shift amount k. It is limited to the range where the data of exists.

<< Modification of Correlation Calculation Process Example 8 >>
Instead of the correlation calculation formula (17) of the correlation calculation processing example 8, the correlation amount C (k) is obtained by the following formula.
C (k) = Σ | (An-1−An) × (An−An + 1) / (Bn−1 + k−Bn + k) × (Bn + k−Bn + 1 + k) − {(An -1 + An) * (An + An + 1)} / {(Bn-1 + k + Bn + k) * (Bn + k + Bn + 1 + k)} |
... (27)
In equation (27), the Σ operation is accumulated for n, and the range taken by n is An-1, An, An + 1, Bn-1 + k, Bn + k, Bn + 1 + k according to the shift amount k. It is limited to the range where the data of exists.

<< Modification of Embodiment >>
3 shows an example in which the focus detection pixels 311 are arranged without a gap, but FIG. 34 shows an image pickup element in which the focus detection pixels 311 are arranged in a line at every other pixel position of the blue pixels of the imaging pixel 310. An example of 211A is shown. Although the density of the focus detection pixels 311 is reduced due to the fact that the focus detection accuracy is slightly reduced by increasing the arrangement interval of the focus detection pixels 311, the image quality obtained by interpolating the image signal at the position of the focus detection pixels 311 is improved. improves.

  In the imaging device 211 illustrated in FIG. 3, an example is illustrated in which a pair of photoelectric conversion units 12 and 13 are provided for each focus detection pixel 311 as illustrated in FIG. 5. FIG. 35 shows focus detection pixels 313 and 314 each having one photoelectric conversion unit in one pixel. The focus detection pixel 313 includes the microlens 10 and the photoelectric conversion unit 16 as illustrated in FIG. Further, the focus detection pixel 314 includes the microlens 10 and the photoelectric conversion unit 17 as illustrated in FIG. The photoelectric conversion units 16 and 17 are projected onto the exit pupil of the interchangeable lens by the microlens 10 to form distance measuring pupils 92 and 93 shown in FIG. Therefore, a pair of image outputs used for focus detection can be obtained by the focus detection pixels 313 and 314.

  FIG. 36 shows an example of an image sensor 211B in which the focus detection pixels 313 and 314 shown in FIGS. 35A and 35B are alternately arranged in a line. A pair of adjacent focus detection pixels 313 and focus detection pixels 314 correspond to the focus detection pixels 311 of the image sensor 211 shown in FIG. 3, and a pair of image outputs used for focus detection can be obtained.

  In the image pickup device 211 shown in FIG. 3, as shown in FIG. 37A, an example in which the image pickup pixels 310 provided with R, G, and B color filters are arranged in a Bayer array is shown. Is not limited to the embodiment described above. For example, as shown in FIG. 37B, G (green), yellow (Ye), magenta (Mg), and cyan (Cy) may be arranged in a complementary color arrangement. When this complementary color filter is used, the focus detection pixel 311 is arranged at a pixel position where cyan and magenta including a blue component whose output error is relatively inconspicuous should be arranged.

  In the image sensor 211 shown in FIG. 3, an example in which the focus detection pixel 311 is not provided with a color filter is shown. However, even if one color filter, for example, a green filter, is provided among the color filters of the same color as the image pickup pixel 310, The invention can be applied.

  In the imaging operation illustrated in FIG. 13, the example in which the image data in which the image signal at the position of the focus detection pixel 311 is corrected by interpolation processing is stored in the memory card 213 is shown. However, the corrected image data is stored in the electronic viewfinder 215 or the body. You may make it display on the back monitor screen not shown provided in the back.

  Note that the imaging elements 211, 211A, and 211B described above can be formed as a CCD image sensor or a CMOS image sensor.

  In the embodiment described above, focus detection by the pupil division method using microlenses has been described as an example. However, the correlation calculation method of the present invention is not limited to the focus detection of the method described above, and re-imaging pupil division is performed. The present invention can be applied to the focus detection of the method, and the effects as described above can be obtained.

  With reference to FIG. 38, focus detection of the re-imaging pupil division method to which the correlation calculation method according to the embodiment of the present invention is applied will be described. In the figure, 191 is an optical axis of the interchangeable lens, 110 and 120 are condenser lenses, 111 and 121 are aperture masks, 112, 113, 122 and 123 are aperture openings, 114, 115, 124 and 125 are re-imaging lenses, 116 126 are image sensors (CCD) for focus detection. Reference numerals 132, 133, 142, and 143 denote focus detection light beams. Reference numeral 190 denotes an exit pupil set at a distance d5 in front of the planned imaging plane of the interchangeable lens. The distance d5 is a distance determined according to the focal lengths of the condenser lenses 110 and 120 and the distances between the condenser lenses 110 and 120 and the aperture openings 112, 113, 122, and 123, and is referred to as a distance measuring pupil distance. Reference numeral 192 denotes a region of the apertures 112 and 122 projected by the condenser lenses 110 and 120 (ranging pupil), and reference numeral 193 denotes a region of the apertures 113 and 123 projected by the condenser lenses 110 and 120 (ranging pupil).

  The condenser lens 110, aperture mask 111, aperture openings 112 and 113, re-imaging lenses 114 and 115, and image sensor 116 are re-imaging pupil division type phase difference detection focus detection units that perform focus detection at one position. Configure. FIG. 38 schematically illustrates a focus detection unit on the optical axis 191 and a focus detection unit outside the optical axis. By combining a plurality of focus detection units, it is possible to realize a focus detection dedicated sensor that performs focus detection by re-imaging pupil division type phase difference detection at the five focus detection positions G1 to G5 shown in FIG. .

  The focus detection unit including the condenser lens 110 is disposed in the vicinity of the condenser lens 110 disposed in the vicinity of the planned imaging plane of the interchangeable lens, the image sensor 116 disposed behind the condenser lens 110, and disposed between the condenser lens 110 and the image sensor 116. A pair of re-imaging lenses 114 and 115 for re-imaging the primary image formed in the vicinity of the imaging plane on the image sensor 116, and a pair disposed in the vicinity (front side in the figure) of the pair of re-imaging lenses. The aperture mask 111 having the aperture apertures 112 and 113. The image sensor 116 is a line sensor in which a plurality of photoelectric conversion units are densely arranged along a straight line, and the arrangement direction of the photoelectric conversion units matches the dividing direction of the pair of distance measuring pupils (= the direction in which the aperture openings are arranged). Let

  Information corresponding to the intensity distribution of the pair of images re-imaged on the image sensor 116 is output from the image sensor 116, and image shift detection calculation processing (correlation processing and phase difference detection processing) to be described later is performed on this information. By applying this, the image shift amount of the pair of images is detected by a so-called pupil division type phase difference detection method (re-imaging method). By multiplying the image shift amount by a predetermined conversion coefficient, the deviation (defocus amount) of the current image plane with respect to the planned image plane is calculated.

  The image sensor 116 is projected on the planned imaging plane by the re-imaging lenses 114 and 115, and the detection accuracy of the defocus amount (image deviation amount) is determined by the detection pitch of the image deviation amount (in the case of the re-imaging method). This is determined by the arrangement pitch of the photoelectric conversion units projected on the planned imaging plane.

  The condenser lens 110 projects the aperture openings 112 and 113 of the aperture mask 111 as areas 192 and 193 on the exit pupil 190. These areas 192 and 193 are called distance measuring pupils. That is, a pair of images re-imaged on the image sensor 116 is formed by a light beam passing through the pair of distance measuring pupils 192 and 193 on the exit pupil 190. The light beams 132 and 133 that pass through the pair of distance measuring pupils 192 and 193 on the exit pupil 190 are referred to as focus detection light beams.

  In addition, the present invention is not limited to focus detection using a pupil division method for a light beam passing through the photographing optical system, and can also be applied to distance measurement using an external light triangulation method, and has the effects described above. Can do. With reference to FIG. 39, distance measurement of an external light triangulation system to which the correlation calculation method according to the embodiment of the present invention is applied will be described. A unit composed of the lens 320 and the image sensor 326 disposed on the imaging surface thereof, and a unit composed of the lens 330 and the image sensor 336 disposed on the imaging surface thereof are disposed with a baseline length therebetween. The pair of units constitutes the distance measuring device 347. An image of the distance measuring object 350 is formed on the image sensors 326 and 336 by the lenses 320 and 330.

  The positional relationship between the images formed on the image sensors 326 and 336 changes according to the distance from the distance measuring device 347 to the distance measuring object 350. Therefore, the relative positional relationship between the two images is detected by performing image shift detection applying the present invention to the signal data of the image sensors 326 and 336, and the distance to the distance measuring object 350 is determined based on this positional relationship. Can be measured. In the external light triangulation method, dirt and raindrops adhere to the lenses 320 and 330, which causes a level difference or distortion in the pair of signals. By applying the correlation calculation method of the present invention, Even if these problems occur, the correlation between the pair of image signal signal data strings output from the image sensors 326 and 336 can be accurately detected.

  In the above description, the correlation calculation uses the sum of the absolute values of the differences between the two data, but other correlation calculation methods may be used. For example, the correlation amount may be calculated by the sum of multiplications of two data, and the relative shift amount between the two signal data strings may be detected from the shift amount that gives the peak value of the correlation amount. Alternatively, the correlation amount may be calculated from the sum of the MAX values of the two data, and the relative shift amount between the two signal data strings may be detected from the shift amount that gives the bottom value of the correlation amount. Furthermore, the correlation amount may be calculated by the sum of the MIN values of the two data, and the relative shift amount between the two signal data strings may be detected from the shift amount that gives the peak value of the correlation amount.

  An image pickup apparatus according to an embodiment of the present invention is not limited to a digital still camera or a film still camera including an interchangeable lens and a camera body, but also to a lens-integrated digital still camera, a film still camera, or a video camera. Can be applied. The present invention can also be applied to a small camera module, a surveillance camera, or the like built in a mobile phone. Furthermore, the present invention can be applied to a focus detection device other than a camera, a distance measuring device, or a stereo distance measuring device.

  The embodiment of the present invention can also be applied to an apparatus that detects the movement of a subject image or camera shake by detecting the correlation between signals of image sensors having different times. Further, it can be applied to pattern matching between an image signal of an image sensor and a specific image signal. Further, the present invention is not limited to detecting the correlation of image signal data, but can be applied to any of the correlations of data related to sound and other generally detecting the correlation of two signals, and the effects described above can be achieved. .

  As described above, in one embodiment, for example, vignetting due to the photographing optical system occurs in one of a pair of focus detection light beams, and a pair of signal data strings output from the image sensor has a relative distortion. Even if it occurs, the correlation between both signal data strings can be detected accurately.

The figure which shows the structure of the digital still camera of one embodiment The figure which shows the focus detection area on the imaging screen which is set to the planned image formation surface of the interchangeable lens Front view showing detailed configuration of image sensor Configuration diagram of imaging pixels Configuration diagram of focus detection pixels The figure which shows the spectral sensitivity characteristic of each color filter of an image pick-up pixel The figure which shows the spectral sensitivity characteristic of a focus detection pixel Cross section of imaging pixel Cross section of focus detection pixel The figure explaining the focus detection method by a pupil division system Front view showing projection relationship on exit pupil plane A graph showing the intensity distribution (light quantity) of an image signal at one focus detection position on the vertical axis and the position deviation within the focus detection position on the horizontal axis. 1 is a flowchart illustrating an imaging operation of a digital still camera (imaging device) according to an embodiment. Flow chart showing details of focus detection operation Diagram explaining correlation calculation The figure for demonstrating the thought of the correlation calculation of one Embodiment The figure which shows the data flow of the correlation calculation process example 1 The figure which shows the case where relative distortion generate | occur | produces in the two signal data strings A and B The figure which shows the result of having performed correlation calculation processing example 1 The figure which shows the data flow of the correlation calculation processing example 2 The figure which shows the result of having performed correlation calculation processing 2 The figure which shows the data flow of correlation calculation processing example 3 The figure which shows the result of having performed correlation calculation processing 3 The figure which shows the data flow of correlation calculation processing 4 The figure which shows the result of having performed correlation calculation processing 4 The figure which shows the data flow of the correlation calculation process 5 The figure which shows the result of having performed correlation calculation processing 5 The figure which shows the data flow of the correlation calculation process 6 The figure which shows the result of having performed correlation calculation processing 6 The figure which shows the data flow of the correlation calculation processing example 7 The figure which shows the result of having performed correlation calculation processing example 7 The figure which shows the data flow of the correlation calculation process example 8. The figure which shows the result of having performed correlation calculation processing example 8 The figure which shows the example of the image pick-up element which arranged the focus detection pixel at the position of the blue pixel of the image pick-up pixel every other pixel in a line. The figure which shows the focus detection pixel provided with one photoelectric conversion part in one pixel FIG. 35 is a diagram illustrating an example of an image sensor in which the focus detection pixels illustrated in FIGS. 35A and 35B are alternately arranged in a line. It is a figure which shows a Bayer arrangement | sequence and a complementary color arrangement | sequence. The figure explaining the focus detection of the re-imaging pupil division system to which the correlation calculation method of one embodiment of the present invention is applied The figure explaining the distance measurement of the external light triangulation system to which the correlation calculation method of one embodiment of the present invention is applied

Explanation of symbols

202 Interchangeable lens 209 Lens drive control device 211 Image sensor 212 Camera drive control device

Claims (19)

First photoelectric conversion means for photoelectrically converting an image of a light beam that has passed through the imaging optical system and outputting a first electric signal data string in which a plurality of electric signal data are sequentially arranged;
A second photoelectric conversion means for photoelectrically converting an image of the light beam that has passed through the imaging optical system and outputting a second electric signal data sequence in which a plurality of electric signal data are sequentially arranged;
Wherein the first electrical signal data string a first target electrical signal data first electrical signal data in, the target first electrical signal data and the first in an electric signal data train, the target first electrical signal data The first calculation data and the second calculation data are respectively calculated by performing the first calculation and the second calculation on at least one first vicinity electric signal data in the vicinity of the first calculation data, and the first calculation data is calculated as the first calculation data. First calculation means for calculating third calculation data by dividing by two calculation data, and sequentially shifting the first electric signal data of interest in the first electric signal data string to generate a third calculation data string ;
The second electrical signal data corresponding to the first electrical signal data of interest in the second electrical signal data sequence and at least one second in the vicinity of the second electrical signal data in the second electrical signal data sequence . The fourth calculation data and the fifth calculation data are respectively calculated by performing the first calculation and the second calculation on the neighboring electric signal data, respectively, and the fourth calculation data is divided by the fifth calculation data. Calculating second calculation data, sequentially shifting the second electric signal corresponding to the shift of the first electric signal data of interest, and generating a sixth calculation data string ;
The degree of correlation between the third calculation data string and the sixth calculation data string is determined by relatively shifting the third calculation data string and the sixth calculation data string, and the first electric signal data string and the second calculation data string are compared. As a degree of correlation with the electrical signal data string, a correlation degree calculating means for calculating,
In the first calculation, the first calculation data as the first calculation result for the attention first electric signal data and the first neighboring electric signal data includes at least the attention first electric signal data, and the second calculation The fourth calculation data that is the first calculation result for the electric signal data and the second neighboring electric signal data is an operation that includes at least the second electric signal data,
In the second calculation, the second calculation data as the second calculation result for the first electric signal data of interest and the first neighboring electric signal data includes at least the first neighboring electric signal data, A correlation calculation device, wherein the fifth calculation data, which is the second calculation result for the electric signal data and the second neighboring electric signal data, is a calculation that includes at least the second neighboring electric signal data. . The correlation calculation device according to claim 1,
The second operation is an operation of adding the first electric signal data of interest and the first neighboring electric signal data, and an operation of adding the second electric signal data and the second neighboring electric signal data. A correlation calculation device characterized by the above. The correlation calculation device according to claim 1,
Characterized in that said second calculation is the average operation between the target first averaging operation of the electrical signal data and the first near electrical signal data, and the second electrical signal data and the second near the electrical signal data Correlation calculation device. The correlation calculation device according to claim 1 ,
The correlation computing means with respect to said third operation data and the sixth arithmetic data, have rows weighted according to the smaller value of the said second operation data fifth operation data, the The degree of correlation between the third calculation data string and the sixth calculation data string is calculated while relatively shifting the weighted third calculation data string and the weighted sixth calculation data string. Correlation calculator. In the correlation calculation device according to any one of claims 1 to 3 ,
The first operation is correlation operation wherein said is of interest first subtraction electrical signal data for the first neighboring electrical signal data, and subtract a said second electrical signal data for the second neighboring electric signal data apparatus. In the correlation calculation device according to any one of claims 1 to 3 ,
The first calculation is a differential calculation for the first electric signal data of interest and the first neighboring electric signal data, and a differentiation calculation for the second electric signal data and the second neighboring electric signal data. Correlation calculator. In the correlation calculation device according to any one of claims 1 to 6,
The correlation calculation unit is configured to integrate an absolute value of a difference between the third calculation data and the sixth calculation data. In the correlation calculation device according to any one of claims 1 to 7 ,
Before executing the first calculation and the second calculation by the first calculation means and the second calculation means, the respective high frequency components for the first electric signal data string and the second electric signal data string A correlation calculation device further comprising high-frequency component removal calculation means for performing calculation for removing. First photoelectric conversion means for photoelectrically converting an image of a light beam that has passed through the imaging optical system and outputting a first electric signal data string in which a plurality of electric signal data are sequentially arranged;
A second photoelectric conversion means for photoelectrically converting an image of the light beam that has passed through the imaging optical system and outputting a second electric signal data sequence in which a plurality of electric signal data are sequentially arranged;
Wherein the first electrical signal data string a first target electrical signal data first electrical signal data in, the target first electrical signal data and the first in an electric signal data train, the target first electrical signal data The first calculation data is calculated by performing a first calculation on at least one first neighboring electric signal data in the vicinity of and corresponding to the attention first electric signal data in the second electric signal data string Second calculation data by performing the first calculation on the second electric signal data to be performed and at least one second neighboring electric signal data in the vicinity of the second electric signal data in the second electric signal data string calculates said first by dividing the calculation data in the second operation data to calculate a third operation data, the noted first electrical signal data and the second electrical signal data to each of the first electrical signal data string in Sequentially shifting in beauty second in an electric signal sequence, a first computing means for generating a third operation data sequence,
A second calculation is performed on the first electric signal data of interest and the first neighboring electric signal data in the first electric signal data string to calculate fourth calculation data, and the second electric signal data string The fifth calculation data is calculated by performing the second calculation on the second electric signal data and the second neighboring electric signal data therein, and the fourth calculation data is divided by the fifth calculation data. 6th operation data is calculated, and the noted 1st electric signal data and the 2nd electric signal data are sequentially shifted in the 1st electric signal data sequence and the 2nd electric signal sequence, respectively, and the 6th operation data sequence is generated. Second calculating means for performing,
The degree of correlation between the third calculation data string and the sixth calculation data string is determined by relatively shifting the third calculation data string and the sixth calculation data string, and the correlation between the first electric signal data string and the second calculation data string is determined. As a degree of correlation with the electrical signal data string, a correlation degree calculating means for calculating,
In the first calculation, the first calculation data as the first calculation result for the attention first electric signal data and the first neighboring electric signal data includes at least the attention first electric signal data, and the second calculation The second calculation data that is the first calculation result for the electric signal data and the second neighboring electric signal data is an operation that includes at least the second electric signal data,
In the second calculation, the fourth calculation data as the second calculation result for the first electric signal data of interest and the first neighboring electric signal data includes at least the first neighboring electric signal data. A correlation calculation device, wherein the fifth calculation data, which is the second calculation result for the electric signal data and the second neighboring electric signal data, is a calculation that includes at least the second neighboring electric signal data. . The correlation calculation device according to claim 9 ,
The first calculation is a subtraction for the attention first electric signal data and the first neighboring electric signal data, and a subtraction for the second electric signal data and the second neighboring electric signal data,
The second calculation is an addition to the first electric signal data of interest and the first neighboring electric signal data, and an addition to the second electric signal data and the second neighboring electric signal data. apparatus. The correlation calculation device according to claim 9 ,
The correlation computing means with respect to said third operation data and the sixth arithmetic data, have rows weighted according to the smaller value of the said second operation data fifth operation data, the The degree of correlation between the third calculation data string and the sixth calculation data string is calculated while relatively shifting the weighted third calculation data string and the weighted sixth calculation data string. Correlation calculator. In the correlation calculation device according to any one of claims 9 to 11 ,
The first calculation includes a differentiation operation on the first electric signal data of interest and the first neighboring electric signal data, and a differentiation operation on the second electric signal data and the second neighboring electric signal data. Correlation calculation device. In the correlation calculation device according to any one of claims 9 to 11 ,
The correlation calculation unit is configured to integrate an absolute value of a difference between the third calculation data and the sixth calculation data. In the correlation calculation device according to any one of claims 9 to 13 ,
Before executing the first calculation and the second calculation by the first calculation means and the second calculation means, the respective high frequency components are applied to the first electric signal data string and the second electric signal data string. A correlation calculation device further comprising high-frequency component removal calculation means for performing calculation for removing. Photoelectric conversion means for receiving a pair of light beams that have passed through a pair of pupil regions of the photographing optical system and outputting first and second electrical signal data strings each composed of a plurality of electrical signals;
Wherein the first electrical signal data string a first target electrical signal data first electrical signal data in, the target first electrical signal data and the first in an electric signal data train, the target first electrical signal data The first calculation data and the second calculation data are respectively calculated by performing the first calculation and the second calculation on at least one first vicinity electric signal data in the vicinity of the first calculation data, and the first calculation data is calculated as the first calculation data. First calculation means for calculating third calculation data by dividing by two calculation data, and sequentially shifting the first electric signal data of interest in the first electric signal data string to generate a third calculation data string ;
The second electrical signal data corresponding to the first electrical signal data of interest in the second electrical signal data sequence and at least one second in the vicinity of the second electrical signal data in the second electrical signal data sequence . The fourth calculation data and the fifth calculation data are respectively calculated by performing the first calculation and the second calculation on the neighboring electric signal data, respectively, and the fourth calculation data is divided by the fifth calculation data. Calculating second calculation data, sequentially shifting the second electric signal corresponding to the shift of the first electric signal data of interest, and generating a sixth calculation data string ;
The degree of correlation between the third calculation data string and the sixth calculation data string is determined by relatively shifting the third calculation data string and the sixth calculation data string, and the first electric signal data string and the second calculation data string are compared. Correlation degree calculating means for calculating as a correlation degree with the electric signal data string,
A focus detection unit that detects a focus adjustment state of the imaging optical system based on the correlation calculated by the correlation calculation unit;
In the first calculation, the first calculation data as the first calculation result for the attention first electric signal data and the first neighboring electric signal data includes at least the attention first electric signal data, and the second calculation The fourth calculation data that is the first calculation result for the electric signal data and the second neighboring electric signal data is an operation that includes at least the second electric signal data,
In the second calculation, the second calculation data as the second calculation result for the first electric signal data of interest and the first neighboring electric signal data includes at least the first neighboring electric signal data, The focus detection apparatus, wherein the fifth calculation data, which is the second calculation result for the electric signal data and the second neighboring electric signal data, is a calculation that includes at least the second neighboring electric signal data. . Photoelectric conversion means for receiving a pair of light beams that have passed through a pair of pupil regions of the photographing optical system and outputting first and second electrical signal data strings each composed of a plurality of electrical signals;
Wherein the first electrical signal data string a first target electrical signal data first electrical signal data in, the target first electrical signal data and the first in an electric signal data train, the target first electrical signal data The first calculation data is calculated by performing a first calculation on at least one first neighboring electric signal data in the vicinity of and corresponding to the attention first electric signal data in the second electric signal data string Second calculation data by performing the first calculation on the second electric signal data to be performed and at least one second neighboring electric signal data in the vicinity of the second electric signal data in the second electric signal data string calculates said first by dividing the calculation data in the second operation data to calculate a third operation data, the noted first electrical signal data and the second electrical signal data to each of the first electrical signal data string in Sequentially shifting in beauty second in an electric signal sequence, a first computing means for generating a third operation data sequence,
A second calculation is performed on the first electric signal data of interest and the first neighboring electric signal data in the first electric signal data string to calculate fourth calculation data, and the second electric signal data string The fifth calculation data is calculated by performing the second calculation on the second electric signal data and the second neighboring electric signal data therein, and the fourth calculation data is divided by the fifth calculation data. 6th operation data is calculated, and the noted 1st electric signal data and the 2nd electric signal data are sequentially shifted in the 1st electric signal data sequence and the 2nd electric signal sequence, respectively, and the 6th operation data sequence is generated. Second calculating means for performing,
The degree of correlation between the third calculation data string and the sixth calculation data string is determined by relatively shifting the third calculation data string and the sixth calculation data string, and the correlation between the first electric signal data string and the second calculation data string is determined. Correlation degree calculating means for calculating as a correlation degree with the electric signal data string,
A focus detection unit that detects a focus adjustment state of the imaging optical system based on the correlation calculated by the correlation calculation unit;
In the first calculation, the first calculation data as the first calculation result for the attention first electric signal data and the first neighboring electric signal data includes at least the attention first electric signal data, and the second calculation The second calculation data that is the first calculation result for the electric signal data and the second neighboring electric signal data is an operation that includes at least the second electric signal data,
In the second calculation, the fourth calculation data as the second calculation result for the first electric signal data of interest and the first neighboring electric signal data includes at least the first neighboring electric signal data. The focus detection apparatus, wherein the fifth calculation data, which is the second calculation result for the electric signal data and the second neighboring electric signal data, is a calculation that includes at least the second neighboring electric signal data. . The focus detection apparatus according to claim 15 or 16 ,
The photoelectric conversion means includes a plurality of first photoelectric conversion units that receive one of the pair of light beams that have passed through the pair of pupil regions of the photographing optical system, and a plurality of second light that receives the other light beam. Including a photoelectric conversion unit,
Each of the first photoelectric conversion units receives the one light flux through a microlens,
Each of the first photoelectric conversion units receives the other light beam via a microlens, and the focus detection device. The focus detection apparatus according to claim 15 or 16 ,
A pair of re-imaging optical systems that re-image the pair of light beams that have passed through the pair of pupil regions of the photographing optical system,
The pair of re-imaging optical systems re-images the optical images formed by the photographing optical system,
The photoelectric conversion means includes a plurality of first photoelectric conversion units that receive a light image re-imaged by one of the pair of re-imaging optical systems, and re-image by the other of the pair of re-imaging optical systems. And a plurality of second photoelectric conversion units that receive the optical image. An imaging apparatus comprising the focus detection apparatus according to any one of claims 15 to 18 .

Images