JP2017097218A - Image shake correction device, image shake correction method, imaging device, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To highly accurately perform parallel shake correction.SOLUTION: An image shake correction device for correcting shake of an image captured by an imaging device 101 comprises a CPU 150 which acquires information on a first parallel shake amount on the basis of information on angular speed and acceleration of the imaging device, acquires information on a second parallel shake amount on the basis of a motion vector of a subject in the image, detects a focus range of the subject in the image, multiplies the second parallel shake amount by a correction coefficient and adds the first parallel shake amount to the second parallel shake amount by which the correction coefficient is multiplied. A correction coefficient in the case where a ratio of the focus range is less than a threshold value is set to be larger than that in the case where the ratio of the focus range is equal to or more than the threshold value.SELECTED DRAWING: Figure 2

Description

  The present invention relates to an image blur correction apparatus, an image blur correction method, an imaging apparatus, and a program that correct image blur due to camera shake or the like.

  Patent Document 1 determines a correction gain for correcting the amount of parallel shake based on the ratio of the subject to the entire image, and obtains a combined value of the amount of angular shake and the value obtained by correcting the amount of parallel shake with the correction gain. Based on this, an anti-vibration control device that drives the shake correction means is proposed.

JP 2011-615721 A

  According to Patent Document 1, since the correction gain is set to be larger as the ratio of the subject to the entire image is larger, there is a concern that the correction gain becomes smaller and the parallel shake amount remains at the time of macro photography where the subject is in a narrow focus range. There is. In addition, since the conventional parallel shake amount information was obtained based on the information of the angular velocity meter and the accelerometer, the detection accuracy of the parallel shake amount is low especially for the low frequency vibration, and the parallel shake amount is high. Correction could not be performed.

  An object of the present invention is to provide an image shake correction apparatus, an image shake correction method, an imaging apparatus, and a program capable of performing highly accurate parallel shake correction.

  An image shake correction apparatus according to the present invention corrects a shake of an image captured by the imaging device based on information on an angular shake amount caused by rotation of the imaging device and a parallel shake amount caused by parallel movement of the imaging device. A first acquisition unit configured to acquire information on a first parallel shake amount based on information on an angular velocity and an acceleration of the imaging apparatus, and a subject motion vector selected on the basis of information on a motion vector in the image Subject vector selection means, second acquisition means for obtaining information on the second parallel shake amount based on the motion vector of the subject, and focus range detection means for detecting the focus range of the subject in the image. The multiplication means for multiplying the second parallel shake amount by the correction coefficient, the first parallel shake quantity, and the second parallel shake quantity multiplied by the correction coefficient by the multiplication means are added. The setting means for setting a correction amount for correcting the shake of the image and the multiplication means, the correction coefficient when the ratio of the focus range detected by the focus range detection means is less than a threshold value, It is set to be larger than the correction coefficient when the ratio of the focusing range is equal to or greater than a threshold value.

  According to the present invention, it is possible to provide an image shake correction apparatus, an image shake correction method, an imaging apparatus, and a program that can perform highly accurate parallel shake correction.

It is the upper side figure and side view of the imaging device by this embodiment. FIG. 2 is a control block diagram of the image blur correction apparatus shown in FIG. 1. It is a figure for demonstrating the parallel shake correction in this embodiment. It is a figure for demonstrating the vector detection in a screen. It is a graph which shows the relationship between the multiplier shown in FIG. 2, and a vector reliability determination part. 3 is a flowchart for explaining the operation of the image shake correction apparatus shown in FIG. 1.

  2. Description of the Related Art Conventionally, an image shake correction apparatus that moves a part of an image shake correction lens or an image sensor in a direction perpendicular to an optical axis based on an angular velocity detected by an angular velocity meter is known. In close-up shooting (shooting conditions with high shooting magnification such as macro shooting), image degradation caused by so-called parallel shake that is parallel or perpendicular to the optical axis of the camera, which cannot be detected with an angular velocity meter alone, is ignored. Can not. For example, it is active when a subject is photographed as close to 20 cm as in macro photography or when the focal length of the photographing optical system is very large (for example, 400 mm) even if the subject is located at about 1 m. Therefore, it is necessary to perform correction by detecting parallel shake.

  There are two types of shake applied to the image pickup device: angular shake due to rotation around the rotation center and parallel shake due to parallel movement of the image pickup device. Deterioration of the image due to angular shake increases as the subject distance and the focal length of the imaging device increase. Image degradation due to parallel shake is related to the subject distance and focal length, and the amount of degradation increases as the image magnification increases (subject distance is closer and focal length is longer).

  Under general shooting conditions (for example, subject distance of 1 m), the influence of image deterioration due to parallel shake can be almost ignored. However, in close-up shooting (for example, subject distance of 10 cm), image deterioration due to parallel shake is caused by a high shooting magnification. It cannot be ignored. For this reason, parallel shake is detected (for example, an optical image stabilization system is detected using an accelerometer or the like, and an electronic image stabilization system detects an image shift), and the image shake is corrected according to the result. Objects with various shooting distances are mixed in the screen. If image blur correction is performed according to the shooting distance of the subject, image deterioration due to parallel shake can be prevented for the subject, but sufficient blur correction cannot be performed for subjects at other shooting distances such as the background. Causes deterioration.

  FIG. 1A is a plan view showing an imaging apparatus 101 according to the present embodiment, and FIG. 1B is a side view thereof. The imaging apparatus 101 includes an image shake correction apparatus that performs shake correction for shakes indicated by arrows 103p and 103y (hereinafter, “angle shakes”) and shakes indicated by arrows 104p and 104y (hereinafter, “parallel shakes”). . The image shake correction apparatus corrects the shake of an image captured by the imaging apparatus based on the angular shake amount and the parallel shake amount.

  Reference numeral 105 denotes a release button (S1), reference numeral 106 denotes a photometric unit, reference numeral 107 denotes an image sensor, and reference numeral 150 denotes a camera CPU.

  The release button 105 transmits the SW1 signal to the CPU 150 in response to the half press by the user, and transmits the SW2 signal to the CPU 150 in response to the full press by the user. The release button 105 functions as an instruction means for instructing shooting preparation and shooting. In this embodiment, half-pressing the release button 105 corresponds to a shooting preparation instruction, and full-pressing the release button 105 corresponds to a shooting instruction.

  The photometry unit (luminance value information acquisition means) 106 measures the amount of light (luminance) that has passed through the imaging optical system using the output from the imaging element 107 and transmits the luminance value information to the CPU 150.

  The image pickup element 107 is configured by a photoelectric conversion element such as a CCD sensor or a CMOS sensor, and picks up an object by photoelectrically converting an optical image formed by the image pickup optical system. An analog electrical signal output from the image sensor 107 is converted into a digital signal by an A / D converter (not shown), and the digital signal is input to an image processing unit (not shown). The image processing unit performs predetermined processing such as white balance and γ processing on the digital signal and transmits the result to the CPU 150. The image processing means includes a motion vector detection unit 180 described later.

  The CPU 150 is a control unit that controls the operation of each unit of the imaging apparatus 101, and includes a microcomputer. The CPU 150 starts shooting preparation operations such as AE (auto focus), image blur correction, AWB (auto white balance) processing, EF (flash pre-flash) processing, face detection, and the like according to the SW1 signal. Further, the CPU 150 drives a shutter drive circuit (not shown) in accordance with the SW2 signal, guides the photographing light flux to the image sensor 107, and performs exposure (photographing). Further, the CPU 150 controls a series of photographing processing operations from reading a signal from the image sensor 107 to writing image data in the image recording unit in accordance with the SW2 signal.

  Reference numerals 108p and 108y denote angular velocity meters (angular velocity detection means) for detecting angular fluctuations around the arrows 108pa and 108ya, respectively. Reference numerals 109p and 109y denote accelerometers (acceleration detecting means) for detecting parallel shakes indicated by arrows 109pa and 109ya, respectively. p represents pitch and y represents yaw.

  A lens driving unit 112 freely drives the image blur correction lens 111 in the directions of the arrows 110p and 110y, and performs image blur correction based on both the angular blur and the parallel blur. The outputs of the angular velocity meters 108p and 108y and the accelerometers 109p and 109y are input to the CPU 150. The driving by the lens driving unit 112 is controlled by the CPU 150.

  The image blur correction lens 111 is an example of an image blur correction unit and constitutes an imaging optical system. The image blur correction lens 111 is moved by the lens driving unit 112 in a direction orthogonal to the optical axis 102 to decenter the optical axis 102 to correct the image blur. The “perpendicular direction” only needs to have a component orthogonal to the optical axis 102 and may be moved obliquely to the optical axis 102. The position of the image blur correction lens 111 is detected by a position detector 113 described later, and the detection signal of the position detector 113 is converted by an A / D converter 114 described later and input to the CPU 150.

  The imaging optical system forms an optical image of a subject (subject image) on the imaging surface of the image sensor 107, and includes a zoom lens (magnification lens), a diaphragm, a focus lens, and the like. The zoom lens (magnification lens) is moved in the optical axis direction to change the focal length. The stop is disposed at the exit pupil position of the imaging optical system, and is driven by a driving unit (not shown) to adjust the amount of light incident on the imaging element 107. The focus lens is moved in the optical axis direction to adjust the focus.

  In the present embodiment, optical image stabilization that moves the image blur correction lens 111 in a plane perpendicular to the optical axis based on the calculated correction amount is used as the image blur correction unit. However, the correction method is a method of preventing shake by moving the image sensor in a plane perpendicular to the optical axis, and reducing the influence of shake by changing the cutout position of each shooting frame output by the image sensor. Electronic vibration isolation, a combination thereof, or the like may be used.

  FIG. 2 is a control block diagram of the image blur correction apparatus according to the present embodiment. The image shake correction apparatus shown in the figure includes a photometry unit 106, an angular velocity meter 108p, an accelerometer 109p, a CPU 150, a motion vector detection unit 180, a lens drive unit 112, an image shake correction lens 111, a position detection unit 113, and an A / D conversion. Part 114. FIG. 2 shows only the configuration of shake (pitch direction: directions of arrows 103p and 104p in FIG. 1) generated in the vertical direction of the imaging apparatus 101. However, a similar configuration is also provided for shake (yaw direction: arrows 103y and 104y directions in FIG. 1) generated in the horizontal direction of the imaging apparatus 101. Since these have basically the same configuration, only the configuration in the pitch direction will be described below.

  CPU 150 includes HPF integration filters 151, 154, 158, sensitivity adjustment unit 152, zoom / focus information acquisition unit 153, gain adjustment unit 155, HPF phase adjustment unit 156, angular velocity BPF unit 157, acceleration BPF unit 159, and comparison unit 160. Have In addition, the CPU 106 includes a parallel shake addition unit 161, a calculation unit 162, a subject vector selection unit 163, a vector calculation unit 164, an integrator 165, a multiplier 166, a subject detection unit 167, a focus range detection unit 168, and a vector reliability determination. A portion 169 is further included.

  In the image shake correction, the angular velocity signal from the angular velocity meter 108p is input to the HPF integration filter 151 of the CPU 150, integrated after the DC component is cut by HPF (high-pass filter or high-pass transmission filter), and converted into an angle signal. Converted. Since the hand-shake frequency band is between 1 Hz and 10 Hz, the HPF has, for example, a primary HPF characteristic that cuts a frequency component sufficiently separated from the hand-shake frequency band, for example, 0.1 Hz or less.

  The output of the HPF integration filter 151 and the information acquired by the zoom / focus information acquisition unit 153 are input to the sensitivity adjustment unit 152. The sensitivity adjustment unit 152 amplifies the output of the HPF integration filter 151 based on information obtained from the zoom / focus information acquisition unit 153, and generates an angle shake correction target value (angle shake correction amount). Accordingly, it is possible to correct a change in shake correction sensitivity, which is a ratio of a shake amount on the image plane to a movement amount of the image shake correction lens 111 due to a change in optical information such as focus and zoom of the imaging optical system. The CPU 150 outputs the corrected angular shake correction target value to the lens driving unit 112 and drives the image shake correction lens 111 to correct the image shake.

  FIG. 3 is a diagram illustrating the angular shake 103p and the parallel shake 104p applied to the imaging apparatus 101. The relationship of the rotation radius L in the case where the parallel shake Y (104p), the angular shake θ (103p), and the rotation center O at the principal point position of the imaging optical system of the camera 101 are determined is as follows (1) (2) (3 ) Expression. The rotation radius L is a distance from the rotation center O to the accelerometer 109p.

Y = Lθ (1)
V = Lω (2)
A = Lωa (3)
Equation (1) represents the rotation radius L when the output Y of the accelerometer 109p is second-order integrated to obtain the displacement Y, and the angular velocity meter 108p is first-order integrated to obtain the angle θ. Equation (2) is the turning radius L when the output of the accelerometer 109p is first-order integrated to determine the velocity V, and the angular velocity ω is determined from the output of the angular velocity meter 108p. Equation (3) is the rotation radius L when the acceleration A is obtained from the output of the accelerometer 109p and the angular acceleration ωa is obtained by first-order differentiation of the output of the angular velocity meter 108p. The rotation radius L can be obtained by any of these methods.

  On the other hand, the shake δ generated on the imaging surface is obtained by the equation (4) from the parallel shake Y at the principal point position of the imaging optical system, the shake angle θ of the imaging optical system, the focal length f of the imaging optical system, and the imaging magnification β.

δ = (1 + β) fθ + βY (4)
Here, the focal length f can be obtained from information acquired by a zoom / focus information acquisition unit 153 that acquires zoom / focus information of the imaging optical system. The imaging magnification β represents the magnification of the size of the subject image formed on the image sensor 107 corresponding to the size of the subject on the screen, and this is also acquired by the zoom / focus information acquisition unit 153. It can be determined by information. The deflection angle θ can be obtained from the integration result of the angular velocity meter 108p. Therefore, angle shake correction can be performed from these pieces of information. That is, θ is output from the HPF integration filter 151, and the sensitivity adjustment unit 152 multiplies θ by (1 + β) f, and outputs (1 + β) fθ in the first term on the right side to the synthesis calculation unit 154.

  Since the second term on the right side is obtained from the second-order integral value Y of the accelerometer 109p and the imaging magnification β, parallel shake correction can be performed according to the information.

  In the present embodiment, a value obtained by adding the first parallel shake amount and the second parallel shake amount is set as the parallel shake amount of the image. Patent Document 1 uses only the first translational shake amount, and conventionally, the second translational shake amount is not taken into consideration, and the translational shake correction cannot be performed with high accuracy. In the present embodiment, high-accuracy parallel shake correction is realized by considering the second parallel shake amount.

  The first translational shake amount is a translational shake amount obtained based on information on the angular velocity of the imaging device detected by the angular velocity meter 108p and the acceleration of the imaging device detected by the accelerometer 109p, and includes the components 154 to 160. Obtained by the first obtaining means. The second translational shake amount is a translational shake amount obtained based on the motion vector of the subject, and is acquired by the second acquisition unit including the components 163 to 168.

  The angular velocity meter 108p and the accelerometer 109p are difficult to accurately measure the low frequency region of the vibration applied to the imaging device 101. On the other hand, the motion vector detection unit 180 can measure the low frequency region more accurately. However, since the measurement result of the motion vector detection unit 180 is easily affected by an error due to the ratio of the subject in the screen and the luminance, in this embodiment, Y = Y · Kv is set and a correction coefficient ( Correction gain) Kv is adjusted.

  In obtaining the first parallel shake amount, the angular velocity signal from the angular velocity meter 108p is input to the HPF integration filter 154, and after the DC component is cut by the HPF, the angular velocity signal is integrated and converted into an angle signal. The output of the HPF integration filter 154 is input to a gain adjustment unit (gain adjustment filter) 155. The gain adjustment unit 155 and the HPF integration filter 154 adjust the gain and phase characteristics in the frequency band where parallel shake correction is to be performed.

  The output of the angular velocity meter 108p is also input to the HPF phase adjustment unit (phase adjustment filter) 156, and the DC component superimposed on the output of the angular velocity meter 108p is cut and the phase of the signal is adjusted. The cut-off frequency here is matched with the cut-off frequency of the HPF of the HPF integration filter 158 described later, and is set so that the frequency characteristics match. From the output of the HPF phase adjustment unit 156, only the frequency component of a predetermined band is extracted by an angular velocity BPF unit (bandpass filter or band transmission filter) 157 that is a band transmission unit.

  The output of the accelerometer 109p is input to the HPF integration filter 158. After the DC component is cut by the HPF, the output is integrated and converted into a speed signal. The cutoff frequency of the HPF at this time is set together with the frequency characteristic of the HPF of the HPF phase adjustment unit 156 as described above. From the output of the HPF integration filter 158, only a frequency component in a predetermined band is extracted by an acceleration BPF unit (bandpass filter or bandpass filter) 159 which is a bandpass means.

  The outputs of the angular velocity BPF unit 157 and the acceleration BPF unit 159 are input to the comparison unit 160, and a correction amount (correction coefficient) for correcting the output of the gain adjustment unit 155 is calculated. The comparison unit 160 obtains L = V / ω from the equation (2). Further, from the equations (1) and (4), δ = (1 + β) fθ + βLθ. Therefore, the gain adjustment unit 155 creates the first parallel shake amount by multiplying θ acquired from the HPF integration filter 154 by β acquired from the zoom / focus information acquisition unit and L acquired from the comparison unit 160. .

  The motion vector detection unit (motion vector detection means) 180 is based on the luminance signal included in the image signal obtained from the image sensor 107 and the luminance signal included in the video signal of the previous field stored in the image memory. Detect vectors. The motion vector can be detected using, for example, a block matching method. In the block matching method, an image signal is divided into a plurality of block areas of an appropriate size, a difference between pixels in a certain range in the previous field (or frame) is calculated for each block, and the sum of absolute values of the differences is calculated. Search for the block in the previous field (or frame) that minimizes. The relative shift between the screens indicates the motion vector of the block. The motion vector obtained by the motion vector detection unit 180 is input to the subject vector selection unit (subject vector selection means) 163.

  Based on the subject detected by the subject detection unit 167, the subject vector selection unit 163 selects and outputs a motion vector of the subject from among the motion vectors detected by the motion vector detection unit 180.

  FIG. 4A is a diagram for explaining a method of detecting a motion vector in the screen. As shown in FIG. 4A, when the focus range of the subject O is narrow, the second parallel shake correction difference between the subject O and the background becomes conspicuous. In the screen, n blocks 10 for detecting vectors are arranged in the horizontal direction on the screen and m in the vertical direction on the screen. Reference numeral 11 denotes an AF frame indicating a focus detection range. Since the motion vector detection unit 180 cannot distinguish between the detected vector and the subject or the background vector, the motion vector detection unit 180 distinguishes the subject and the background vector by comparing the angular velocity and the frequency distribution of the vector using the angular velocity information.

  FIG. 4B is a histogram showing angular velocity and vector frequency distribution, where the horizontal axis represents angular velocity and the vertical axis represents frequency. 12 represents a subject vector, 13 represents a background vector, and 14 represents angular velocity. Ideally, if the angular velocity of the subject O matches the angular velocity of the imaging device 101, the subject O appears to stop when viewed from the imaging device 101, so the angular velocity becomes 0 dps. Since the background is moving at the angular velocity of the image pickup apparatus 101, for example, if panning is performed at 10 dps, the angular velocity of the background is 10 dps. Thus, the vector near the angular velocity 14 is the background vector 13, and the vector away from the angular velocity 14 is the subject vector 12. Since the user aligns the AF frame 11 with the subject O, the user weights the vectors detected by the blocks 10 around the AF frame 11 to increase the accuracy of the subject and background vector extraction. The focus range detection unit (synthesis range detection means) 168 can detect the frequency distribution range near the subject vector 12 shown in FIG. 4B as the focus range.

  The subject detection unit 167 may distinguish between the subject and the background vector using the angular velocity information and the information of the AF frame 11, but the subject detection unit 167 uses the subject frame information displayed using the subject discrimination information such as face recognition. May be used. The subject vector discriminated by the subject vector selection unit 163 is output to the vector calculation unit 164.

  The focus range detection unit 168 detects the focus range of the subject O in the screen. From the focus range detection unit 168, information on the ratio of the subject to the entire angle of view (the ratio of the subject in the image) is obtained. For example, the ratio of the subject with respect to the entire angle of view may be calculated by dividing the subject vector 12 in the screen by all the vectors using the block 10 and the subject detection unit 167, or from the zoom position and the subject distance information. You may calculate using the imaging | photography magnification calculated | required. In FIG. 4A, the focus range detection unit 168 can recognize the range of the subject O inside the AF frame 11 as the focus range.

  The vector calculation unit (vector calculation means) 164 converts the input vector into an angular velocity using focal length and frame rate information, and outputs it to the integrator (integration means) 165. The integrator 165 converts the angular velocity into angle information by integrating the angular velocity. Multiplier (multiplier) 166 multiplies this by imaging magnification β acquired from the zoom / focus information acquisition unit and correction coefficient (correction gain) Kv as a vector feedback gain, and outputs the result to parallel shake addition unit 161. As the correction coefficient Kv, a value that can be varied from 0 to 1 is selected based on the outputs of the focus range detection unit 168 and the vector reliability determination unit 169.

  The multiplier 158 sets the correction coefficient Kv when the ratio of the focus range of the subject in the image detected by the focus range detection unit 168 is less than the threshold, larger than the correction coefficient Kv when the ratio is equal to or greater than the threshold. doing. In this embodiment, the correction coefficient Kv is set to 0 (zero) when the ratio of the focus range of the subject is equal to or greater than the threshold, and the correction coefficient Kv is set to 1 when the ratio is less than the threshold. However, the present invention is not limited to this.

  In Patent Document 1, the correction gain is set to be larger as the proportion of the subject in the entire image increases, thereby balancing the subject image blur correction and the background image blur correction during moving image shooting. However, when the ratio of the subject to the entire image is small, the correction gain becomes small, the correction of the parallel shake amount is not effective, and there is a concern that the influence of the parallel shake remains at the time of macro photography where the focus range of the subject is narrow. According to the present embodiment, it is possible to perform appropriate shake correction even when the focus range of the subject is narrow under close-up shooting conditions.

  The vector reliability determination unit 169 determines whether the vector output from the motion vector detection unit 180 is a vector that has been correctly detected. The vector reliability determination unit 169 determines whether the luminance detected by the photometry unit 106 is less than a threshold value. Vector detection is difficult for image signals where the feature points of an object are difficult to understand, such as low contrast. Therefore, when the vector reliability determination unit 169 outputs the error value from the motion vector detection unit 180, the multiplier 158 sets a correction gain Kv smaller than 1 to prevent the image blur correction from being overcorrected. The multiplier 158 sets the correction coefficient Kv when the luminance value of the image is less than the threshold value smaller than the correction coefficient Kv when the luminance value is equal to or more than the threshold value.

  FIG. 5 is a graph showing the relationship between the multiplier 158 and the vector reliability determination unit 169. The horizontal axis represents the vector reliability that is the output of the vector reliability determination unit 169, and the vertical axis represents the correction coefficient Kv. However, the horizontal axis may be replaced with a luminance value.

  Multiplier 158 determines a correction coefficient based on the detection results of motion vector detection unit 180 and photometry unit 106 and multiplies the output of integrator 165. When the vector determination value output for each field is less than the threshold value T1, the multiplier 158 sets a correction gain of about 0.3 times. For example, this is the case of a shooting scene in which the detection accuracy of the motion vector detection unit 180 is reduced in a night shooting scene or the like. Next, when the vector determination value is not less than the threshold value T1 and less than T2, the multiplier 158 sets a correction coefficient of about 0.8 times. For example, this is a case of a shooting scene (for example, ISO sensitivity of 1200 or more) in which the ISO sensitivity of the imaging apparatus 101 is increased and noise becomes noticeable and affects vector detection. When the vector determination value is equal to or greater than the threshold value T2, it is determined that the vector detection is correctly performed, and the parallel shake correction is positively performed. Therefore, the multiplier 158 sets a correction gain of 1 time.

  The parallel shake addition unit 161 sets a correction amount for correcting the shake of the image by adding the output of the gain adjustment unit 155 (first parallel shake amount) and the output of the multiplication value 166 (second parallel shake amount). Setting means (adding means). The calculation unit 162 adds the output from the sensitivity adjustment unit 152 (angle shake amount) and the output from the parallel shake addition unit 161 (composite parallel shake amount), and sets a correction amount for correcting image shake. , Calculating means for subtracting the output (current correction value) of the A / D converter 114.

  FIG. 6 illustrates an image blur correction method (processing from detection of the subject vector 12 to calculation of an image blur correction amount, which is calculated at a constant interrupt period after the camera is turned on) by the image blur correction apparatus (CPU 150). It is a flowchart of. “S” represents a step. The flowchart shown in FIG. 6 can be embodied as a program for causing a computer to execute each step. Such a program can be stored in a storage means such as a non-transitory computer-readable storage medium. Note that the image blur correction method of the present embodiment can be applied to both moving image shooting and still image shooting.

  In S600, the CPU 150 determines whether image blur correction is enabled (whether an unillustrated anti-shake switch is turned on and the SW1 signal is generated). If there is, the process ends. In S601, the CPU 150 obtains information detected by the angular velocity meters 108p and 108y and detected by the accelerometers 109p and 109y. In S602, the CPU 150 calculates an angular shake amount (angle shake correction amount) using output values of the angular velocity meters 108p and 108y, focal length information, and the like.

  In S603, the CPU 150 arranges a vector detection block in the screen by the template matching method, and detects a motion vector in the screen based on a difference from the previous frame. In S604, the CPU 150 distinguishes between the subject and the background vector using the frequency distribution of the vector and the angular velocity. In S <b> 605, the CPU 150 converts the detected vector into angular information by performing angular velocity conversion on the detected vector and then integrating the converted vector. In S606, the CPU 150 determines an error of the detected vector. If the ratio of the in-focus range and the brightness value with respect to all the vectors are equal to or greater than the threshold value, the process proceeds to S608, and if either is less than the threshold value, the process proceeds to S607.

  In S607, since the vector has been correctly detected, the CPU 150 sets a correction coefficient Kv of about 1 time. In S608, the CPU 150 sets a correction coefficient Kv smaller than 1 to prevent overcorrection.

  In S609, the CPU 150 determines whether the ratio of the in-focus range of the subject in the image is less than the threshold value. If it is equal to or greater than the threshold, the process proceeds to S610, and if it is less than the threshold, the process proceeds to S611. In S610, since the focus range is narrow, the parallel shake correction difference with the background is conspicuous. Therefore, the CPU 150 calculates the translational shake correction amount by adding the angle-converted vector to the output of the gain adjustment unit 155. In step S611, the CPU 150 adds the parallel shake correction including the vector to the angular shake correction, and drives the image shake correction lens 111 as a final shake correction amount. On the other hand, if it is equal to or greater than the threshold value, the subject's focusing range is wide, so the parallel shake correction difference from the background is not noticeable. Therefore, the CPU 150 adds the parallel shake correction amount and the angular shake correction amount without performing vector feedback, and drives the image shake correction lens 111 as a final shake correction amount. According to the present embodiment, when the focus range of the subject is less than the threshold value, the accuracy of the parallel shake correction can be improved by adding the vector to the parallel shake correction amount.

  As mentioned above, although embodiment of this invention was described, a various deformation | transformation and change are possible for this invention within the range of the summary. The present invention supplies a program that realizes one or more functions of the above-described embodiments to a system or apparatus via a network or a storage medium, and one or more processors in a computer of the system or apparatus read and execute the program This process can be realized. It can also be realized by a circuit (for example, ASIC) that realizes one or more functions.

  The present invention is not limited to image blur correction apparatuses for digital single-lens reflex cameras and digital compact cameras, but can also be installed in photographing apparatuses such as surveillance cameras, Web cameras, and mobile phones.

DESCRIPTION OF SYMBOLS 151 ... HPF integral filter, 152 ... Sensitivity adjustment part, 161 ... Parallel shake addition part (addition means), 162 ... Calculation part (calculation means), 168 ... Synthesis range detection part (synthesis range detection means), 180 ... Motion vector Detection unit (motion vector detection means)

Claims (15)

An image shake correction apparatus that corrects a shake of an image captured by the imaging device based on information on an angular shake amount caused by rotation of the imaging device and a parallel shake amount caused by parallel movement of the imaging device,
First acquisition means for acquiring information on a first parallel shake amount based on information on angular velocity and acceleration of the imaging device;
Subject vector selection means for selecting a motion vector of a subject based on information on a motion vector in the image;
Second acquisition means for acquiring information of a second parallel shake amount based on the motion vector of the subject;
Focusing range detecting means for detecting a focusing range of the subject in the image;
Multiplying means for multiplying the second parallel shake amount by a correction coefficient;
Setting means for setting a correction amount for correcting shake of the image by adding the first parallel shake amount and the second parallel shake amount multiplied by the correction coefficient by the multiplication unit;
The multiplying unit is configured so that the correction coefficient when the ratio of the focus range detected by the focus range detection unit is less than a threshold is greater than the correction coefficient when the ratio of the focus range is greater than or equal to the threshold. An image blur correction device characterized by being set large.   The image blur correction apparatus according to claim 1, wherein the multiplying unit sets the correction coefficient when the ratio of the in-focus range is equal to or greater than a threshold value to zero. The second acquisition means includes
Vector computing means for converting the motion vector of the subject into angular velocity;
Integrating means for converting the angular velocity converted by the vector calculating means into angle information;
The image blur correction apparatus according to claim 1, wherein: A motion vector detecting means for detecting a motion vector in the image;
The object vector selection means selects the motion vector of the object based on the information on the motion vector detected by the motion vector detection means. The image blur correction apparatus described. Further comprising luminance value information acquisition means for acquiring information of luminance values of the image;
The multiplication unit sets the correction coefficient when the luminance value acquired by the luminance value information acquisition unit is less than a threshold value to be smaller than the correction coefficient when the luminance value is equal to or greater than the threshold value. The image blur correction device according to any one of claims 1 to 4.   The image blur correction apparatus according to claim 4, wherein the focus range detection unit detects the focus range based on a frequency distribution of vectors detected by the motion vector detection unit.   6. The focus range detection unit according to claim 1, wherein the focus range detection unit detects the focus range based on a shooting magnification calculated from a focal length and a subject distance of the imaging apparatus. Image shake correction device.   The image blur correction apparatus according to claim 4, wherein the subject vector selection unit selects a motion vector of the subject based on a frequency distribution of vectors detected by the motion vector detection unit. An image shake correction apparatus that corrects a shake of an image captured by the imaging device based on information on an angular shake amount caused by rotation of the imaging device and a parallel shake amount caused by parallel movement of the imaging device,
Subject vector selection means for selecting a motion vector of a subject based on a motion vector in the image;
Obtaining means for obtaining information on the amount of parallel shake based on a motion vector of the subject selected by the subject vector selecting means;
An image blur correction apparatus comprising: Focusing range detecting means for detecting a focusing range of the subject in the image;
Multiplying means for multiplying the parallel shake amount acquired by the acquiring means by a correction coefficient;
Further comprising
The multiplying unit is configured so that the correction coefficient when the ratio of the focus range detected by the focus range detection unit is less than a threshold is greater than the correction coefficient when the ratio of the focus range is greater than or equal to the threshold. The image blur correction apparatus according to claim 9, wherein the image blur correction apparatus is set to be large. Further comprising luminance value information acquisition means for acquiring information of luminance values of the image;
The multiplication unit sets the correction coefficient when the luminance value acquired by the luminance value information acquisition unit is less than a threshold value to be smaller than the correction coefficient when the luminance value is equal to or greater than the threshold value. The image blur correction device according to claim 10.   An image pickup apparatus comprising the image blur correction apparatus according to claim 1. An image shake correction method for correcting shake of an image captured by the imaging device based on information on an angular shake amount caused by rotation of the imaging device and parallel shake amount caused by translation of the imaging device,
Acquiring information on the first parallel shake amount based on information on the angular velocity and acceleration of the imaging device;
Selecting a motion vector of a subject based on motion vector information in the image;
Obtaining information on the second parallel shake amount based on the motion vector of the subject;
Detecting a focusing range of the subject in the image;
Multiplying the second parallel shake amount by a correction coefficient;
Setting a correction amount for correcting blur of the image by adding the first parallel shake amount and the second parallel shake amount multiplied by the correction coefficient;
Have
An image blur correction method, wherein the correction coefficient when the ratio of the in-focus range is less than a threshold is set larger than the correction coefficient when the ratio of the in-focus range is equal to or greater than the threshold. An image shake correction method for correcting shake of an image captured by the imaging device based on information on an angular shake amount caused by rotation of the imaging device and parallel shake amount caused by translation of the imaging device,
Selecting a motion vector of a subject based on motion vector information in the image;
Obtaining information on the amount of parallel shake based on the motion vector of the subject;
An image blur correction method characterized by comprising:   A program for causing a computer to execute the image blur correction method according to claim 13 or 14.