JP4803982B2 - Image processing apparatus, image recording apparatus, and image processing method - Google Patents

Description

  The present invention relates to an image processing device, an image recording device, and an image processing method, and more particularly to an image processing device, an image recording device, and an image processing method that adaptively perform gradation conversion processing on an image.

  The gradation expression of the image is one of the important factors that determine the image quality. Usually, the signal output from the image sensor is substantially proportional to the amount of light incident on the image sensor. Here, the output signal from the image sensor is subjected to some gradation conversion processing in accordance with the final image observation environment (for example, image observation with a monitor or image observation with a printer output) in subsequent image processing. . For example, in the case of a general digital camera, the sRGB color space is adopted as the standard color space of the image file format, but the gradation of an image shot in the case of the digital camera is a gamma characteristic (sRGB specification) ( It is designed to be optimal when displayed on a monitor having γ = 2.2).

  Usually, the gradation conversion characteristics of an image are fixed to one type for each input device such as a digital camera, or are generally selected by a user or the like from a plurality of gradation conversion characteristics. In recent years, a technique for adaptively optimizing gradation conversion characteristics for individual images in accordance with the luminance distribution of the image (or scene) is being used. This is because the dynamic range of the scene varies from scene to scene, so that the luminance information of the scene is converted to the dynamics of output devices such as monitors and printers when converted with uniform gradation conversion characteristics without taking this difference into account. This is because it is difficult to efficiently reflect the range.

  One technique for adaptively optimizing tone conversion characteristics for individual images is a histogram equalization method. This is because gradation conversion is performed so that the luminance histogram (frequency number of each luminance gradation level) of the image is made uniform, thereby increasing the amount of luminance information held by the image, and efficiently applying gradation to the output device. The technology to assign.

  Here, if such gradation conversion is uniformly applied regardless of shooting conditions and scenes, for example, the noise in the dark portion is amplified by the gradation conversion and exceeds an allowable level. It may be converted.

As an example of the solution, the technique proposed in Patent Document 1 detects the luminance distribution of an image, determines whether the luminance distribution needs to be corrected based on the detected luminance distribution, and corrects the luminance distribution. When it is determined that the luminance distribution is necessary, the luminance distribution is corrected to be uniform, thereby preventing the output image from being deteriorated.
JP 2003-179809 A

  However, since the technique proposed in Patent Document 1 determines the necessity of correcting the luminance distribution from the luminance distribution of the subject, for example, an image having low scene luminance and containing a lot of noise due to electrical amplification. For images shot with a specified subject type (landscape, person, etc.), the gradation conversion characteristics and the optimum values after gradation conversion differ depending on the shooting conditions. It is difficult to perform a tone conversion process.

  The present invention has been made in view of the above circumstances, and provides an image processing apparatus and an image processing method capable of performing a gradation conversion process most suitable for a scene at the time of shooting regardless of shooting conditions. Objective.

In order to achieve the above object, an image processing apparatus according to a first aspect of the present invention includes a histogram calculation unit that calculates a histogram of pixel values of input image data, and the histogram calculation unit that calculates the histogram. Gradation conversion characteristic determining means for determining gradation conversion characteristics when performing gradation conversion processing on the image data based on the histogram and photographing information when the image data is photographed; and the gradation conversion characteristics Gradation conversion means for gradation-converting the input image data based on the gradation conversion characteristics determined by the determination means, wherein the gradation conversion characteristic determination means has the gradation conversion characteristics when determining, from the photographing information sought reciprocal of the noise amount after the gradation conversion, in the histogram calculated by said histogram calculating means, the frequency value after the gradation conversion Neu The larger portion than the reciprocal of the amount of further comprises a histogram correction means corrects for limiting the reciprocal of the noise amount after the gradation conversion, shooting information to be used for the above histogram correction, the image data is captured And at least one of noise reduction processing information indicating whether or not noise reduction processing has been performed on the image data.

In order to achieve the above object, an image recording apparatus according to a second aspect of the present invention includes an imaging unit that captures an image of an object scene to obtain image data, and pixel values of image data obtained by the imaging unit. A gradation when performing a gradation conversion process on the image data based on a histogram calculating means for calculating a histogram, and the histogram calculated by the histogram calculating means and shooting information when the image data is shot Gradation conversion characteristic determining means for determining a conversion characteristic; gradation conversion means for gradation converting the input image data based on the gradation conversion characteristic determined by the gradation conversion characteristic determination means; Recording means for recording the image data subjected to gradation conversion by the gradation conversion means on a recording medium, and the gradation conversion characteristic determination means determines the gradation conversion characteristics when determining the gradation conversion characteristics. Obtains the reciprocal of the noise amount after the gradation conversion from behind the information, the in the histogram calculated by the histogram calculation unit, said portions frequency value is greater than the reciprocal of the noise amount after the gradation conversion gradation It further includes histogram correction means for performing correction to limit the reciprocal of the noise amount after conversion, and the shooting information used for correcting the histogram includes shooting sensitivity information when the image data is shot and image data. And at least one of noise reduction processing information indicating whether or not noise reduction processing has been performed.

In order to achieve the above object, an image processing method according to a third aspect of the present invention includes a histogram calculation step of calculating a histogram of pixel values of input image data, and the histogram calculated in the histogram calculation step. A gradation conversion characteristic determining step for determining a gradation conversion characteristic when performing gradation conversion processing on the image data based on the image information when the image data is captured, and the gradation conversion characteristic determining step A gradation conversion step for gradation-converting the input image data based on the gradation conversion characteristic determined in step (2), wherein the gradation conversion characteristic determination step is performed when the gradation conversion characteristic is determined. In addition, the reciprocal of the noise amount after the gradation conversion is obtained from the shooting information, and the frequency value in the histogram calculated in the histogram calculation step is the value after the gradation conversion. The method further includes a histogram correction step for correcting a portion that is larger than the reciprocal of the noise amount to the reciprocal of the noise amount after the gradation conversion, and the shooting information used in the histogram correction step is obtained by shooting image data. And at least one of noise reduction processing information indicating whether noise reduction processing has been performed on the image data.

  According to these first to third aspects, when determining the gradation conversion characteristics for performing the gradation conversion, the imaging information when the image data is obtained is taken into consideration, so that it does not depend on the imaging conditions. The tone conversion process most suitable for the scene at the time of shooting can be performed.

  According to the present invention, it is possible to provide an image processing apparatus, an image recording apparatus, and an image processing method capable of performing gradation conversion processing most suitable for a scene at the time of shooting regardless of shooting conditions.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
FIG. 1 is a diagram showing a conceptual configuration of an image processing apparatus according to an embodiment of the present invention.

  As shown in FIG. 1, the image processing apparatus includes a histogram calculation unit 1, a tone conversion characteristic determination unit 2, and a tone conversion unit 4. When the image data is input to the histogram calculation unit 1, the histogram calculation unit 1 calculates a histogram of pixel values of the input image data. As the histogram, a histogram of only the luminance component of the image data (luminance histogram) may be calculated, or a histogram for each color component of the image data may be calculated.

  After the histogram is calculated by the histogram calculation unit 1, the calculated histogram is input to the gradation conversion characteristic determination unit 2. The gradation conversion characteristic determination unit 2 determines the gradation conversion characteristic based on the histogram and the photographing information 3 when the image data is photographed. Based on the determined gradation conversion characteristics, the gradation conversion unit 4 performs gradation conversion processing on the input image data and outputs the output image data to the outside.

Hereinafter, the image processing apparatus of FIG. 1 will be described more specifically. FIG. 2 is a block diagram showing a configuration of a digital camera (hereinafter referred to as a camera) as an example of an image recording apparatus including an image processing apparatus according to an embodiment of the present invention.
As shown in FIG. 2, the digital camera includes a microcomputer (abbreviated as “microcomputer” in the figure) 11, an imaging unit 12, an A / D converter (denoted as A / D in the figure) 13, and The bus 14, the RAM 15, the image processing circuit 16, the ROM 17, the recording medium 18, and the operation unit 19.

  The microcomputer 11 is a control unit that performs overall control of the camera. In the microcomputer 11, focus control of the imaging optical system inside the imaging unit 12, exposure control of the imaging device, recording control when recording image data on the recording medium 18, and the like are performed.

  The imaging unit 12 includes a photographing optical system, an imaging element, and a driving unit thereof. The imaging unit 12 converts a light beam from a subject (not shown) that is incident through the photographing optical system into an electrical signal in the imaging element.

  The A / D conversion unit 13 converts the electrical signal obtained by the imaging unit 12 into digital data to generate image data.

  A bus 14 is a transfer path for transferring data such as image data obtained by the A / D converter 13 to each circuit of the camera. The RAM 15 is a memory for temporarily storing data such as image data.

  The image processing circuit 16 is a circuit that performs image processing of input image data input via the bus 14. Here, the image processing circuit 16 includes a white balance (WB) correction unit 20, a synchronization unit 21, a Y / C separation unit 22, a color conversion unit 23, a JPEG compression unit 24, and a histogram calculation unit 25. , The histogram correction unit 26, the histogram accumulation unit 27, the gradation conversion table calculation unit 28, and the gradation conversion unit 29. Here, in the gradation conversion characteristic determination unit 2, the histogram calculation unit 25, the histogram correction unit 26, the histogram accumulation unit 27, and the gradation conversion table calculation unit 28 correspond to each other.

  A ROM 17 serving as noise characteristic storage means and fixed gradation conversion characteristic storage means is a memory in which various control programs executed by the microcomputer 11 and various setting values of the camera are stored. In particular, the ROM 17 of this embodiment stores a default gradation conversion table 30, noise characteristic information 31, and a gradation composition ratio 32.

  The default gradation conversion table 30 is a gradation conversion table having standard characteristics stored in the ROM 17 as fixed characteristics for each camera. An example of the default gradation conversion table 30 is shown by a solid line in FIG. Here, the horizontal axis of FIG. 3 indicates the image input value. Note that the image input values in FIG. 3 are pixel values of the image data input from the A / D converter 13. Also, the vertical axis on the left side of FIG. 3 shows the output value after gradation conversion (8-bit output). The fault gradation conversion table stored in the ROM 17 is not limited to one. For example, a plurality of different default gradation conversion tables may be stored so that the user can arbitrarily select a default gradation conversion table. Alternatively, an optimum default gradation conversion table may be automatically selected from a plurality of default gradation conversion tables depending on the shooting conditions.

  The noise characteristic information 31 is information relating to the noise characteristic, and indicates how much noise appears in what form when an image is taken. The noise characteristic information 31 is information stored as a fixed value in the ROM 17. The noise characteristic information 31 is indicated by a solid line in FIG. Here, the horizontal axis of FIG. 4 indicates the input value. The input value here is also an A / D conversion value in the A / D conversion unit 13 as in FIG. The vertical axis on the left side of FIG. 4 indicates the amount of noise. As shown in FIG. 4, when the input value increases, the amount of noise increases accordingly. In FIG. 4, there is noise even when the input value is 0, which is a dark current component.

  Here, the noise characteristic information 31 is an amount that changes in accordance with shooting sensitivity, temperature, exposure time, and the like at the time of shooting. For example, when the shooting sensitivity at the time of shooting is high, the amount of noise increases. Therefore, a plurality of noise characteristic information corresponding to changes in photographing sensitivity, temperature changes, and exposure times are stored in the ROM 17, and at the time of image data photographing, the photographing sensitivity, temperature, and exposure time at that time are set. The corresponding noise characteristic information may be read out.

  Further, in recent cameras, a camera having a noise reduction processing function for reducing noise of an image at the time of photographing has been proposed. Therefore, noise characteristic information in a state in which noise reduction processing has been performed corresponding thereto is also included in the ROM 17. You may make it memorize in.

  The gradation composition ratio 32 is a composition ratio when the default gradation conversion table 30 and the cumulative histogram described later are combined. FIG. 5 shows an example of the gradation composition ratio 32. As shown in FIG. 5, the gradation synthesis ratio 32 stores a value corresponding to the scene mode. Here, the scene mode is one of shooting modes for shooting with various settings, and is a mode in which a scene at the time of shooting can be set. By setting the scene mode, a setting value suitable for each scene is automatically selected and exposure control or the like is performed. In the present embodiment, as the tone composition ratio corresponding to the scene mode, for example, a standard mode for shooting with standard settings, a landscape mode for shooting with settings suitable for landscape shooting, and a person shooting mode However, the present invention is not limited to this. However, the present invention is not limited to this, although the gradation composition ratio corresponding to the person mode for shooting with the setting and the night view mode for shooting with the setting suitable for night scene shooting is stored.

  The recording medium 18 is a recording medium on which an image processed by the image processing circuit 16 is recorded, and is composed of, for example, a memory card.

  The operation unit 19 is various operation members operated by the user. When the operation unit 19 is operated by the user, various controls are performed by the microcomputer 11 in accordance with the operation state. Here, the operation unit 19 includes, for example, a release button for instructing shooting execution, a selection button for selecting a scene mode, and the like.

  Shooting control in the camera having the configuration as shown in FIG. 2 will be described with reference to FIG. FIG. 6 is a flowchart showing a procedure of imaging control including an image processing method according to an embodiment of the present invention. Here, the flowchart of FIG. 6 is started when the release button is turned on by the user.

  When the release button is turned on by the user, known AE and AF are performed based on the output of the imaging unit 12 (step S1). Thereafter, exposure control is performed (step S2), and an image signal for recording is obtained in the imaging unit 12. Thereafter, an imaging process of the recording image signal obtained in the imaging unit 12 is performed (step S3). In this imaging process, the image signal obtained by the imaging unit 12 is A / D converted by the A / D conversion unit 13. The image data obtained by the A / D conversion unit 13 is input to the WB correction unit 20 of the image processing circuit 16.

  The WB correction unit 20 performs white balance correction on the image data (step S4). In the white balance correction, the R gain and the B gain of the image data are corrected so that the white color of the image input to the WB correction unit 20 is appropriate. The image data that has been subjected to white balance correction in the WB correction unit 20 is input to the synchronization unit 21.

  The synchronization unit 21 performs synchronization processing (step S5). In the synchronization process, image data having the three RGB colors as one pixel component is generated from the image data input to the synchronization unit 21 by interpolation. The image data that has undergone the synchronization processing in the synchronization unit 21 is input to the Y / C separation unit 22.

  The Y / C separation unit 22 performs Y / C separation processing (step S6). In the Y / C separation process, the input image data is separated into a Y (luminance) signal and a C (color) signal. Among the separated signals, the Y signal is input to the histogram calculation unit 25 and the gradation conversion unit 29, and the C signal is input to the color conversion unit 23.

  The color conversion unit 23 performs a color conversion process (step S7). In the color conversion process, the C signal input to the color conversion unit 23 is converted into a standard color signal such as sRGB by a camera or the like. The signal color-converted by the color conversion unit 23 is input to the JPEG compression unit 24.

  In the histogram calculation unit 25, histogram calculation processing is performed (step S8). In the histogram calculation process, a histogram (luminance histogram) is calculated from the frequency value of each luminance input of the Y signal input to the histogram calculation unit 25. The example of the histogram calculated in the histogram calculation part 25 with the continuous line of FIG. 7 is shown. Here, the horizontal axis of FIG. 7 indicates the luminance input value. Further, the vertical axis on the left side of FIG. 7 indicates the luminance distribution, that is, the frequency value of luminance input. The histogram calculated by the histogram calculation unit 25 is input to the histogram correction unit 26.

  In the present embodiment, the histogram is calculated from the luminance component of the image data. However, the histogram of the color component of the image data may be calculated. In this case, a histogram for all three colors of RGB may be calculated, or a histogram for only the G component may be calculated.

  The histogram correction unit 26 performs a histogram correction process (step S9). In the histogram correction process, the histogram calculated by the histogram calculation unit 25 is corrected based on the noise characteristic information 31 stored in the ROM 17.

  The histogram correction process will be described with reference to FIG. In the histogram correction process, first, the default gradation conversion table 30 stored in the ROM 17 is read (step S21). Next, the inclination of the default gradation conversion table 30 is calculated (step S22). Here, the inclination of the default gradation conversion table 30 is obtained by differentiating the default gradation conversion table 30. For example, when the default gradation conversion table 30 is indicated by a solid line in FIG. 3, the inclination is indicated by a broken line in FIG.

  After the inclination of the default gradation conversion table 30 is calculated, the noise characteristic information 31 stored in the ROM 17 is read (step S23). Next, the amount of noise after tone conversion is estimated. The noise amount after gradation conversion is the product of the noise amount and the noise amplification factor after gradation conversion. Here, the amplification factor of the noise after gradation conversion is represented by the slope of the default gradation conversion table 30 calculated in step S22. Therefore, the amount of noise after gradation conversion is the product of the amount of noise indicated by the solid line in FIG. 4 and the slope of the default gradation conversion table indicated by the broken line in FIG. 3, and as a result, the amount of noise after gradation conversion obtained. Is indicated by a broken line in FIG. As indicated by the broken line in FIG. 4, after the tone conversion, the peak of the noise amount comes to a dark portion in the original image. This is because the dark portion of the original image is expanded and the bright portion is compressed by gradation conversion.

  After the noise amount after gradation conversion is estimated, the frequency value restriction level of the histogram is determined in order to correct the histogram (step S24). Here, in the present embodiment, the frequency value of the histogram is limited so that the noise after gradation conversion becomes inconspicuous. For this purpose, the reciprocal of the noise amount after gradation conversion is calculated as the frequency value limit level. This frequency value restriction level is indicated by a broken line in FIG. As shown in FIG. 7, the limit level of the frequency value increases in a portion where the noise amount after gradation conversion increases.

  Here, in the present embodiment, the frequency value limit level of the histogram is the reciprocal of the noise amount after gradation conversion. For example, after calculating the reciprocal, a predetermined calculation is performed to set a more appropriate frequency value limit level. You may make it ask.

  After the frequency value restriction level is determined, the portion of the histogram that exceeds the frequency value restriction level is restricted as shown in FIG. 9 (step S25). By performing tone conversion using the histogram corrected in this way, noise after tone conversion becomes inconspicuous.

  Here, it returns to description of FIG. 6 again. The histogram corrected by the histogram correction unit 26 is input to the histogram accumulation unit 27. The histogram accumulation unit 27 performs a histogram accumulation process (step S10). In the histogram accumulation process, the histograms input to the histogram accumulation unit 27 are sequentially accumulated from the low luminance component side.

  FIG. 10 shows an example of a cumulative histogram. Here, the solid line in FIG. 10 indicates the cumulative histogram before the histogram correction unit 26 corrects the histogram. Also, the broken line in FIG. 10 indicates the cumulative histogram after the histogram correction unit 26 corrects the histogram. However, the cumulative histogram after the histogram correction is normalized so that the maximum value of the cumulative frequency (corresponding to the total number of frequencies) matches the maximum value of the cumulative frequency before the histogram correction. In the cumulative histogram after the histogram correction, the slope of the portion where the amount of noise increases after gradation conversion is gentle compared to the cumulative histogram before the histogram correction.

  The accumulated histogram obtained by the histogram accumulating unit 27 is input to the gradation conversion table calculating unit 28. In the gradation conversion table calculation unit 28, a gradation conversion table calculation process is performed (step S11).

  The gradation conversion table calculation process will be described with reference to FIG. In the tone conversion table calculation process, the accumulated histogram obtained by the histogram accumulating unit 27 and the default tone conversion table 30 stored in the ROM 17 are synthesized at a predetermined synthesis ratio to calculate the tone conversion table. .

  In FIG. 11, first, the scene mode information at the time of shooting is checked (step S31). Next, it is determined which of the tone composition ratios stored in the ROM 17 should be selected according to the scene mode information checked in step S31 (step S32). Next, the default gradation conversion table 30 and the cumulative histogram are combined according to the determined gradation composition ratio (step S33).

  FIG. 12 shows an example of synthesis of the default gradation conversion table 30 and the cumulative histogram. Here, a thin solid line in FIG. 12 indicates a default gradation conversion table, a broken line in FIG. 12 indicates a cumulative histogram, and a thick solid line in FIG. 12 indicates a final gradation conversion table obtained after synthesis. In the example of FIG. 12, the scene mode is the standard mode (gradation composition ratio 0.5: 0.5). That is, in the example of FIG. 12, since the gradation composition ratio is 0.5: 0.5, the gradation conversion table obtained after composition is the average value of the default gradation conversion table 30 and the cumulative histogram.

  Although not shown in FIG. 12, when shooting a subject having a high contrast such as a landscape, a more appropriate gradation expression can be achieved by increasing the ratio of the cumulative histogram. To. Conversely, in the case of a person, the contrast of the subject is originally low, and the default gradation conversion table is emphasized in order to avoid an increase in the contrast more than necessary. Furthermore, in the case of a night view, the ratio of the default gradation conversion table is increased so that originally dark images do not become brighter than necessary. In the case of a night view, the default gradation conversion table and the cumulative histogram may not be combined.

  Note that the gradation composition ratio is not limited to storing only the values corresponding to the scene mode. For example, the gradation composition ratio corresponding to the setting of the strobe mode or the automatic exposure mode is also stored at the same time. You may make it leave. For example, when the strobe is turned on at the time of shooting, the contrast of the image is increased. Therefore, as in a landscape scene, the ratio of the cumulative histogram may be increased to perform tone composition. Further, when exposure is performed manually, composition may be prohibited. Further, tone synthesis may be performed according to whether or not the noise reduction processing function is used. That is, when the noise reduction process is performed, the ratio of the default gradation conversion table is increased.

  Here, it returns to description of FIG. 6 again. The gradation conversion table calculated by the gradation conversion table calculation unit 28 is input to the gradation conversion unit 29. In the gradation conversion unit 29, gradation conversion processing is performed (step S12). In the gradation conversion process, the Y signal input from the Y / C separation unit 22 is subjected to gradation conversion based on the gradation conversion table input from the gradation conversion table calculation unit 28. The Y signal subjected to gradation conversion is input to the JPEG compression unit 24.

  The JPEG compression unit 24 performs JPEG compression of the tone-converted Y signal and the color-converted C signal (step S13). Thereafter, header information such as the shooting information is added to the JPEG compressed data to create an image file (step S14), and the created image file is recorded on the recording medium 18 (step S15). This completes the shooting control. By recording the shooting information in the header information of the image file, the gradation conversion processing described in the present embodiment can be performed in post-processing.

  As described above, according to the present embodiment, since the scene information at the time of shooting can be reflected when calculating the gradation conversion table at the time of gradation conversion, the gradation conversion process most suitable for the shooting scene is performed. Can be applied.

  Although the present invention has been described based on the above embodiments, the present invention is not limited to the above-described embodiments, and various modifications and applications are naturally possible within the scope of the gist of the present invention. For example, although the above-described embodiment has been described only at the time of image shooting, the technique of the present invention can also be applied at the time of image reproduction.

  Further, in the above-described embodiment, the case where the same gradation conversion is performed in one screen has been described. However, one screen is divided into a plurality of regions, and the floor is divided under different conditions for each divided region. A key conversion table may be calculated.

  Further, the above-described embodiments include various stages of the invention, and various inventions can be extracted by appropriately combining a plurality of disclosed constituent elements. For example, even if some constituent requirements are deleted from all the constituent requirements shown in the embodiment, the problem described in the column of the problem to be solved by the invention can be solved, and the effect described in the column of the effect of the invention Can be extracted as an invention.

1 is a diagram illustrating a conceptual configuration of an image processing apparatus according to an embodiment of the present invention. FIG. 2 is a block diagram showing a configuration of a digital camera as an example of an image recording apparatus including an image processing apparatus according to an embodiment of the present invention. It is the figure which showed the example of the default gradation conversion table. It is the figure which showed the example of noise characteristic information. It is the figure which showed the example of the gradation synthetic | combination ratio. 5 is a flowchart illustrating imaging control including an image processing method according to an embodiment of the present invention. It is a figure which shows the example of a histogram. It is a flowchart shown about a histogram correction process. It is a figure shown about the histogram after a frequency value restriction | limiting. It is a figure shown about the example of a cumulative histogram. It is a flowchart shown about a gradation conversion table calculation process. It is a figure which shows the example of a synthesis | combination with a default gradation conversion table and a cumulative histogram.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1,25 ... Histogram calculation part, 2 ... Gradation conversion characteristic determination part, 3 ... Shooting information, 4,29 ... Gradation conversion part, 11 ... Microcomputer (microcomputer), 12 ... Imaging part, 13 ... A / D conversion , 14 ... bus, 15 ... RAM, 16 ... image processing circuit, 17 ... ROM, 18 ... recording medium, 19 ... operation unit, 20 ... white balance (WB) correction unit, 21 ... synchronization unit, 22 ... Y / C separation unit, 23 ... color conversion unit, 24 ... JPEG compression unit, 26 ... histogram correction unit, 27 ... histogram accumulation unit, 28 ... gradation conversion table calculation unit

Claims (6)

Histogram calculation means for calculating a histogram of pixel values of input image data;
Gradation conversion for determining gradation conversion characteristics when performing gradation conversion processing on the image data based on the histogram calculated by the histogram calculation means and photographing information when the image data is photographed Characterization means;
Gradation conversion means for gradation-converting the input image data based on the gradation conversion characteristics determined by the gradation conversion characteristic determination means;
Comprising
The gradation conversion characteristic determining means obtains the reciprocal of the noise amount after the gradation conversion from the photographing information when determining the gradation conversion characteristic , and the frequency calculated in the histogram calculated by the histogram calculating means Histogram correction means for performing correction to limit a portion whose value is larger than the reciprocal of the noise amount after gradation conversion to the reciprocal of the noise amount after gradation conversion ;
The shooting information used when correcting the histogram is at least one of shooting sensitivity information when the image data is shot and noise reduction processing information indicating whether noise reduction processing has been performed on the image data. An image processing apparatus comprising: As noise characteristics of the image data, information on noise characteristics when the image data corresponding to the shooting sensitivity information is shot and information on noise characteristics when the image data corresponding to the noise reduction processing information is shot. Noise characteristics storage means for storing, further comprising
The gradation conversion characteristic determining means includes, in the correction of the histogram, according to the shooting information, information on noise characteristics when the image data corresponding to the shooting sensitivity information is shot and the noise reduction processing information. read any information about noise characteristics when corresponding image data is captured, in the histogram based on the information on the read-out noise characteristic, the frequency value than the reciprocal of the noise amount after the gradation conversion The image processing apparatus according to claim 1, wherein correction is performed to limit a portion that becomes larger . A fixed gradation conversion characteristic storage means for storing at least one fixed gradation conversion characteristic that is uniformly applicable to the image data and has a fixed characteristic;
The gradation conversion characteristic determining means obtains the slope of the fixed gradation conversion characteristic read from the fixed gradation conversion characteristic storage means when the histogram is corrected, and is read from the noise characteristic storage means. We are asking you to reciprocal of the noise amount after the gradation conversion from the noise amount after gradation conversion obtained by the product of the slope of the noise amount and the the obtained fixed gradation conversion characteristic which is information on the noise characteristics The image processing apparatus according to claim 2. An imaging means for capturing an image of the object scene and obtaining image data;
Histogram calculating means for calculating a histogram of pixel values of image data obtained by the imaging means;
A gradation conversion characteristic for determining a gradation conversion characteristic when a gradation conversion process is performed on the image data based on the histogram calculated by the histogram calculation means and photographing information when the image data is photographed. A determination means;
Gradation conversion means for gradation-converting the input image data based on the gradation conversion characteristics determined by the gradation conversion characteristic determination means;
Recording means for recording the image data subjected to gradation conversion by the gradation conversion means on a recording medium;
Comprising
The gradation conversion characteristic determining means obtains the reciprocal of the noise amount after the gradation conversion from the photographing information when determining the gradation conversion characteristic , and the frequency calculated in the histogram calculated by the histogram calculating means Histogram correction means for performing correction to limit a portion whose value is larger than the reciprocal of the noise amount after gradation conversion to the reciprocal of the noise amount after gradation conversion ;
The shooting information used when correcting the histogram is at least one of shooting sensitivity information when the image data is shot and noise reduction processing information indicating whether noise reduction processing has been performed on the image data. An image recording apparatus comprising: A histogram calculation step of calculating a histogram of pixel values of input image data;
Gradation conversion characteristic determination for determining gradation conversion characteristics when performing gradation conversion processing on the image data based on the histogram calculated in the histogram calculation step and photographing information when the image data is photographed Process,
A gradation conversion step for gradation-converting the input image data based on the gradation conversion characteristics determined in the gradation conversion characteristic determination step;
Have
In the gradation conversion characteristic determination step, when determining the gradation conversion characteristic, the reciprocal of the noise amount after the gradation conversion is obtained from the shooting information , and in the histogram calculated in the histogram calculation step , the frequency A histogram correction step of performing correction to limit a portion whose value is larger than the reciprocal of the noise amount after gradation conversion to the reciprocal of the noise amount after gradation conversion ;
The shooting information used in the histogram correction step includes at least one of shooting sensitivity information when the image data is shot and noise reduction processing information indicating whether noise reduction processing has been performed on the image data. An image processing method. When the histogram is corrected in the histogram correction step, the inclination of the fixed gradation conversion characteristic that is uniformly applicable to the image data and has a fixed characteristic is obtained, and the image is captured when the image data is captured It is obtained by the product of the amount of noise corresponding to any of the sensitivity information and the noise reduction processing information indicating whether noise reduction processing has been performed on the image data and the slope of the fixed gradation conversion characteristic obtained above. the image processing method according to claim 5, characterized in that the noise amount after gradation conversion Ru seek reciprocal of the noise amount after the gradation conversion.

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