JP5173664B2 - Image processing apparatus and image processing method - Google Patents

Description

  The present invention relates to a technique for performing correction processing on image data obtained by reading a subject image obtained through an optical lens from an image sensor having a photoelectric conversion function.

FIG. 15 shows a block configuration of a conventional single-lens reflex digital camera. In this configuration, first, a subject image is formed through the photographing lens 302 under the control of the lens control unit 303. The image sensor 312 captures a subject image formed using photoelectric conversion, and the A / D converter 313 performs A / D conversion on the image data output from the image sensor to output digital image data. Next, the aberration correction unit 315 performs processing for correcting the aberration of the photographic lens, and outputs image data in which the optical aberration of the photographic lens is corrected. After correcting the photographic lens aberration, the development processing unit 316 performs various image correction processing such as white balance correction, color conversion processing, contrast conversion (gamma conversion), and sharpness processing. In the example of FIG. 15, the camera body 300 includes a WB correction detection unit 333 and a WB correction coefficient calculation unit 334 for white balance correction processing. The image data subjected to the image correction processing by the development processing unit 316 is recorded on the recording medium 321 by the recording control unit 320. Alternatively, image processing is performed by the output control unit 322 so that image data is optimal for viewing on a display medium such as a display or a color printer, and the image data is output to the display medium 323.

In order to perform optical aberration correction of the taking lens in the aberration correction unit 315, there is a method in which a correction table for optical aberration correction is stored in the camera memory 311 in advance and used. In this way, the camera control unit 310 at the time of photographing reads the correction table from the camera memory 311, sends a correction table in the aberration correction unit 315 performs the aberration correction processing on the image data correcting unit 315 is taken. In particular, as a process for correcting the shading characteristics of a photographed image, a method as disclosed in Patent Document 1 is disclosed. In this document, when image data is captured by scanning a document, shading characteristics including optical characteristics of the capturing device and characteristics of the image sensor are corrected. At that time, data for correcting shading characteristics is created from the data scanned and acquired in advance and stored in the memory. Then, the correction data stored at the time of scanning is read to correct the shading of the scanned image.

  Conventionally, after performing aberration correction on captured image data, detection processing for analyzing images for various image processing, and image correction coefficient for performing image correction processing according to the detection results The process to ask for was performed. In the example of FIG. 15, detection processing by the WB correction detection unit 333 and calculation processing by the WB correction coefficient calculation unit 334 are performed on the image data processed by the aberration correction processing unit 315. On the other hand, the image data after the aberration correction has been temporarily stored in the buffer memory 314.

  However, in the above configuration, the continuous shooting performance, the continuous shooting performance, and the like greatly depend on the processing performance of the aberration correction unit 315. That is, when the time for performing the aberration correction processing of the photographic lens is long, the subsequent development processing, recording processing, and the like are delayed by the processing time. Further, during the aberration correction, it is not possible to input the next shot image data, and it takes time until the next cut in continuous shooting can be shot. In order to maintain the continuous shooting performance and the continuous shooting performance, a buffer memory can be provided in front of the aberration correction unit 315, but the cost and the scale of hardware may be increased.

  An object of the present invention is to solve the above-described problems, and an object thereof is to improve image quality by aberration correction processing while maintaining continuous shooting performance and continuous shooting performance.

To solve the problems described above, the image processing apparatus of the present invention is based on the first correction coefficient for correcting the aberration of the optical lens, an imaging unit that captures a subject image formed through the optical lens A first correction unit that corrects the image data output from the image data, a feature amount detection unit that detects a feature amount from the image data output from the imaging unit that has not been corrected by the first correction unit, and the feature Coefficient calculation means for calculating a second correction coefficient based on the feature quantity detected by the quantity detection means, and second correction means for correcting the image data corrected by the first correction means based on the second correction coefficient. and correcting means comprises a converting means for converting for the calculation of the detection or the second correction coefficient for the first correction factor the feature quantity, the feature quantity detecting unit and the coefficient calculating means calculates the Strange The feature data is detected or the second correction coefficient is calculated using the correction data converted by the means, and the second correction means obtains the second data obtained by using the converted correction data. The image data corrected by the first correction unit is corrected based on the correction coefficient.

The image processing apparatus of the present invention is based on the first correction coefficient for correcting the aberration of the optical lens, corrects the image data output from the imaging means captures a subject image formed through the optical lens a first correcting means for, an instruction means for instructing the detection condition of the feature in accordance with the first correction coefficient, based on the detection conditions instructed by the instruction means, corrected by the first correction means Feature amount detecting means for detecting a feature amount from image data output from the image pickup means that has not been detected, coefficient calculating means for calculating a second correction coefficient based on the feature amount detected by the feature amount detecting means, And a second correction unit that corrects the image data corrected by the first correction unit based on the second correction coefficient calculated by the coefficient calculation unit.

  According to the present invention, it is possible to maintain the continuous shooting performance and the performance of the number of continuous shots and improve the image quality by the aberration correction processing.

  Hereinafter, embodiments according to the present invention will be described in detail with reference to the drawings.

(First embodiment)
FIG. 1 is a block diagram showing a configuration of a single-lens reflex digital camera to which the image processing apparatus of the present invention can be applied. This camera has a lens unit 101 for forming a subject image, and a camera main body 100 that records a captured image as image data on a recording medium 121 or outputs it to a display medium 123 such as a display or a printer. Consists of.

  The subject image is formed by the photographing lens 102, and the formed subject image is captured by the image sensor 112. The image sensor 112 photoelectrically converts the photographed subject image and outputs it as electrical data, and the A / D converter 113 converts this data into digital image data. In order to output the subject image as digital image data in this way, in the photographing lens 102, zoom operation, focusing, aperture control, and the like are controlled by the lens control unit 103. Here, the zoom operation is performed by the user adjusting the focal length by using a zoom mechanism (not shown) provided in the lens, and focusing is performed by an automatic focus mechanism (not shown). As for the aperture, the camera control unit 110 sends the aperture condition set by the user with an operation member (not shown) of the camera body 100 to the lens control unit 103 via the signal line 106. The lens control unit 103 controls the diaphragm attached to the photographing lens 102 according to the information.

  Digital image data captured by the image sensor 112 and subjected to A / D conversion 113 is temporarily stored in the buffer memory 114. The image data up to this point is data having aberration of the taking lens, here, distortion of drop in peripheral light amount. The aberration correction unit 115 performs peripheral light amount drop correction (first correction) on the image data. The aberration correction unit 115 performs peripheral light loss correction by multiplying each image data by a gain (first correction coefficient) that varies depending on the distance from the center of the screen based on the position of each pixel in the image data in the screen. Do. Each gain data is sent from the camera control unit 110 to the aberration correction unit 115 through the signal line 152.

  An example of gain data here is shown in FIG. It consists of gain data represented by 10 dots with respect to the distance (image height) from the center of the screen. For pixel data located between 10 image heights, a gain interpolated with gains at 2 points of image height between 2 points where the corresponding pixel data is located is used.

  In the present embodiment, the lens unit 101 can be exchanged, and aberration characteristics differ from lens unit to lens unit. Therefore, this 10-point gain table is given an ID for each interchangeable lens unit 101 and its characteristics are obtained in advance.

As described above, this characteristic varies depending on the focal length of the lens, the shooting distance to the in-focus position, and the stop, and is configured by a four-dimensional table as shown in FIG. Each of these correction coefficients is mainly obtained from an actually captured image or a value obtained by simulating an actually captured image by ray tracing from a design value.
FIG. 3 shows 11 points of gain data corresponding to 11 image heights. However, since the gain is always 1.0 at the center of the screen, that is, when the image height is 0, 10 points are omitted. This can be dealt with by giving gain data. For example, when the aperture is F4.0, data obtained by performing 1: 2 interpolation between the table for the image height of the aperture F2.8 and the table for the image height of the aperture F8 is used. Similarly, when the shooting distance is 2.0 m, 1: 1 interpolation is performed between the tables at 1.0 m and 3.0 m for the image height obtained at the time of the aperture stop. Further, when the focal length is 50 mm, the table at 50 mm is used with respect to the image height under the conditions of the aperture and shooting distance obtained above. Thereby, the gain of 10 points with respect to the image height is determined.

  The table in FIG. 3 is stored in the camera memory 111 and needs to correspond to all the photographing lenses 101 that can be attached to the camera main body 100. Therefore, it is necessary to have a table corresponding to the lens ID information. When the table of FIG. 3 is stored in a memory in the lens 101 (not shown), since each photographing lens 101 has the table of FIG. 3, it is not necessary to correspond to the lens ID information. Using the peripheral light amount drop correction table prepared as described above, the aberration correction unit 115 performs a peripheral light amount drop correction process.

  In the peripheral light amount drop correction, each pixel on the entire screen is multiplied by a gain for the image height shown in FIG. 2 corresponding to the position of the pixel. For a pixel located between 10 points, a gain interpolated with gains of 2 points sandwiching the pixel is used. As a result, as shown in FIG. 4, the original digital image data 401 when the uniform luminance surface is photographed is corrected so as to have a uniform screen as 402 with respect to the image height.

  In the present embodiment, the development processing unit 116 performs four processes, which are white balance processing, brightness and contrast correction processing, face brightness correction processing, and dark portion correction processing, which are image processing. For these processes, the main unit 100 includes a feature amount detection block 130 that detects various feature amounts from the captured image data, and a correction coefficient for each image process based on the feature amounts obtained in this block. The correction coefficient calculation block 131 is calculated. Here, the feature amount detection block 130 includes a WB (white balance) detection unit 133, a histogram detection unit 135, a face detection unit 137, and a dark part correction detection unit 139. The correction coefficient calculation block 131 includes a WB correction coefficient calculation unit 134, a brightness / contrast correction coefficient calculation unit 136, a face brightness correction coefficient calculation unit 138, and a dark part correction coefficient calculation unit 140.

  Next, the parallel processing of the aberration correction processing by the aberration correction unit 115 and the detection processing and calculation processing by the feature amount detection block 130 and the correction coefficient calculation block 131, which are features of the present embodiment, will be described.

  First, white balance processing performed by the WB detection unit 133, the WB correction coefficient calculation unit 134, and the development processing unit 116 will be described.

  In the WB detection unit 133, the captured image is divided into two-dimensional blocks for each of a plurality of pixels in order to automatically perform white balance from the captured image. Then, as shown in FIG. 5, the integration is performed in the block for each of the R pixel 501, the G1 pixel 502, the G2 pixel 503, and the B pixel 504, and the R: G1: G2: B color ratio is obtained from the integration result in the block. Ask for. Further, for example, on the two-dimensional coordinates of the color ratios R: (G1 + G2) and B: (G1 + G2), a line indicating the black body radiation trajectory characteristic of R: (G1 + G2): B of the image sensor is examined in advance. Then, a block having a color ratio that is a coordinate located in the vicinity of the line is determined as an achromatic color block, and R, G1 + G2, and B in the block of only the block determined as an achromatic color are further integrated, and the color ratio R : (G1 + G2): B is obtained and set as the color ratio of the white component of the entire screen. The WB correction coefficient calculation unit 134 obtains a white balance coefficient for making this color ratio 1: 1: 1 from the color ratio of the image obtained here, and sends the coefficient to the development processing unit 116 for development processing. In the unit 116, white balance correction processing is performed.

  In this embodiment, while the white balance detection process and the white balance coefficient calculation process are performed on the captured digital image data, the peripheral light amount drop correction process is performed in the aberration correction processing unit 115 via the buffer memory 114 in parallel. . As a result, the processing time until all of the aberration correction process, the white balance detection process, and the white balance coefficient calculation process are completed can be shortened. Therefore, it is possible to improve the shooting performance such that the continuous shooting interval can be increased and the number of continuous shots can be increased.

  However, since the captured image input to the WB detection unit 133 is image data before aberration correction, it still has distortion due to a decrease in peripheral light amount. Therefore, at the time of white balance processing, it is necessary to reflect the amount of distortion due to the decrease in peripheral light amount.

  In the present embodiment, the correction coefficient conversion unit 141 converts the peripheral light amount drop correction data read from the camera control unit 110 into a peripheral light amount drop correction gain that can be used for WB detection by level bit number conversion, dimension change, or the like. To do. The WB detection unit 133 performs detection processing using the converted peripheral light amount drop correction gain.

  FIG. 6 is a diagram for explaining an example thereof, and shows the relationship between the entire screen of the captured image and the division block to be processed. In FIG. 6, it is assumed that the WB detection unit 133 calculates a color ratio for white balance detection of a block at a position 602, for example, and determines that 602 is an achromatic block. At this time, when achromatic blocks are collected and integrated for each of R, G1, G2, and B, the distance from the screen center 601 to the 602 block center 603 is obtained, and the peripheral light loss correction gain having the same image height as that length is blocked. The R, G1, G2, and B integral values are multiplied. As a result, the amount of distortion due to the loss of peripheral light amount is reflected in the detection result for white balance correction.

  Next, brightness and contrast correction processing performed by the histogram detection unit 135, the brightness / contrast correction coefficient calculation unit 136, and the development processing unit 116 will be described.

  First, the histogram detection unit 135 obtains a histogram by integrating the frequency for each pixel value over the entire image of the captured digital image data. Based on the histogram, the brightness / contrast correction coefficient calculation unit 136 adjusts the brightness and contrast of the entire image.

  For example, as shown in FIG. 7 (a), a histogram with a low luminance distribution and a dark image as a whole is desired to be a bright image with a high luminance distribution as shown in FIG. 7 (b). And In this case, as shown in FIG. 8, it is necessary to correct the characteristics so that the output image data after correction becomes larger than the input image data before correction.

  Further, as shown in FIG. 9A, the scene is a backlight scene, and the histogram is mainly distributed in two places near the low luminance and the high luminance, and the distribution near the low luminance of the image is corrected. Assume that it is desired to brighten a portion near low luminance as shown in FIG. When such contrast correction is performed, it is necessary to perform correction by multiplying a gain having a characteristic such that an input / output relationship as shown in FIG. 10 is obtained.

  In this embodiment, while the histogram detection process and the brightness / contrast correction coefficient calculation process are performed on the photographed digital image data, the aberration correction processing unit 115 passes the buffer memory 114 in parallel and performs the peripheral light amount drop correction process. To do. As a result, the processing time until all of the aberration correction processing, histogram detection processing, and brightness / contrast correction coefficient calculation processing are completed can be shortened. Therefore, it is possible to improve the shooting performance such that the continuous shooting interval can be increased and the number of continuous shots can be increased.

  However, since the captured image input to the histogram detection unit 135 is image data before aberration correction, it still has distortion due to a decrease in peripheral light amount. Therefore, at the time of brightness / contrast correction, it is necessary to reflect the amount of distortion caused by a decrease in the amount of peripheral light.

  In the present embodiment, the correction coefficient conversion unit 141 converts the peripheral light amount drop correction data read from the camera control unit 110 into a peripheral light amount drop correction gain that can be used for histogram detection by converting the number of bits of a level, changing a dimension, or the like. To do. Then, the histogram detection unit 135 performs detection processing using the converted peripheral light amount drop correction gain.

  The histogram detection unit 136 inputs the peripheral light amount drop correction gain converted by the correction coefficient conversion unit 141 when obtaining the frequency distribution of the uncorrected images in FIGS. 7A and 9A. Then, the histogram detection unit 135 obtains the frequency distribution of the pixel values after multiplying the peripheral light amount drop correction gain according to the position of each pixel value of the input image data. By obtaining the histogram in this way, it is possible to perform brightness / contrast correction processing reflecting the peripheral light amount drop correction.

Next, the face brightness correction process performed by the face detection unit 137, the face brightness correction coefficient calculation unit 138, and the development processing unit 116 will be described.
First, the face detection unit 137 detects the position and brightness of the face from the captured image data. Then, the face brightness correction coefficient calculation unit 138 calculates a coefficient for correcting the face brightness to an appropriate preferable brightness based on the face position information and the face brightness information obtained here. .

  In this embodiment, while the face detection process and the face brightness correction coefficient calculation process are performed on the captured digital image data, the peripheral light amount drop correction process is performed in the aberration correction processing unit 115 via the buffer memory 114 in parallel. Do. As a result, the processing time until all of the aberration correction processing, face detection processing, and face brightness correction coefficient calculation processing are completed can be shortened. Therefore, it is possible to improve the shooting performance such that the continuous shooting interval can be increased and the number of continuous shots can be increased.

  However, since the captured image input to the face detection unit 137 is image data before aberration correction, it still has distortion due to a decrease in peripheral light amount. Therefore, when correcting the face brightness, it is necessary to reflect the amount of distortion due to the decrease in peripheral light amount.

  In the present embodiment, the correction coefficient conversion unit 141 converts the peripheral light amount drop correction data read from the camera control unit 110 by level bit number conversion, dimension change, or the like. That is, the correction data is converted into a peripheral light amount drop correction gain that can be used for face detection and a peripheral light amount drop correction gain that can be used to calculate a face brightness correction coefficient.

  The face detection unit 137 obtains the peripheral light amount drop correction gain from the correction coefficient conversion unit 141 and corrects the brightness around the screen before performing face detection. Thereby, the information of the low-luminance face reflected in the peripheral part of the image can also be obtained accurately.

  Further, the face brightness correction coefficient calculation unit 138 obtains the image height position using the face position information with respect to the detected face brightness value, and multiplies the peripheral light amount drop correction gain to thereby calculate the peripheral brightness. A coefficient for correcting the brightness of the face after correcting the light loss is obtained.

  The development processing unit 116 uses the coefficients obtained as a result of the above processing to perform gain correction to reach the target face brightness, thereby correcting the brightness of the face reflecting the peripheral light amount drop correction. Correction processing can be performed appropriately.

  Next, the dark part correction processing performed by the dark part correction detection unit 139, the dark part correction coefficient calculation unit 140, and the development processing unit 116 will be described.

  For example, when a part of a photographed image is larger and darker than its peripheral part, there are scenes that need to be corrected to brighten the dark part and correct the contrast of the image to be flat. For example, a scene in which the main subject is photographed with backlight is an example. The dark portion correction processing of the present embodiment is processing processing for setting such a scene to appropriate brightness as a whole, and details of the processing will be described below.

  FIG. 11 shows the entire screen of an image to be processed by the dark portion correction detection unit 139, and the screen is divided into a large block 1104 and a small block 1102. Then, an average value AveL of the pixel values in the large block and an average value AveS of the pixel values in the small block are obtained. The dark portion correction coefficient calculation unit 140 calculates a gain to be applied to the pixel value P for each pixel from the relationship between each pixel value and AveL and AveS. The development processing unit 116 performs correction based on the gain value, so that dark portion contrast correction can be performed.

  Here, a gain GL for the average value in the large block, a gain GS for the average value in the small block, and a gain Gp for each pixel value are used. As shown in FIG. 12, when each gain GL, GS, Gp is given to AveL, AveS, P, a gain value that decreases as the value increases and increases as the value decreases, each pixel of the correction result to be obtained. The value Yp is expressed by the following equation.

Yp = (GL * KL + GS * KS + Gp * Kp) * P
Here, KL, KS, and Kp are fixed design tuning values for optimizing the image data generated by the gains GL, GS, and Gp so that the appearance is preferable, and are obtained from captured images of various scenes. There are things.

  By performing the correction as described above, it is possible to perform contrast adjustment so as to correct the brightness of the main subject which is a dark portion when the main subject such as a backlight scene is dark and the periphery thereof is bright.

  In this embodiment, while the dark portion correction detection processing and dark portion correction coefficient calculation processing are performed on the captured digital image data, the peripheral light amount drop correction processing is performed in the aberration correction processing portion 115 via the buffer memory 114 in parallel. . As a result, the processing time until all of the aberration correction processing, dark portion correction detection processing, and dark portion correction coefficient calculation processing are completed can be shortened. Therefore, it is possible to improve the shooting performance such that the continuous shooting interval can be increased and the number of continuous shots can be increased.

  However, since the photographed image input to the dark part correction detection unit 139 is image data before aberration correction, it still has distortion due to a decrease in peripheral light amount. Therefore, it is necessary to reflect the amount of distortion due to the decrease in the amount of peripheral light when correcting the dark part.

  In the present embodiment, the peripheral light amount drop correction gain that the correction coefficient conversion unit 141 can use for the dark portion correction coefficient calculation by converting the peripheral light amount drop correction data read from the camera control unit 110 by, for example, level bit number conversion or dimension change. Convert to Then, the dark portion correction coefficient calculation unit 140 performs a calculation process using the converted peripheral light amount drop correction gain.

  The dark portion correction coefficient calculation unit 140 reflects the gains GL, GS, and Gp in the above equations. That is, the gain corresponding to the image height position of the peripheral light amount drop correction is applied to the values AveL, AveS, and P of the respective blocks and pixels by their positions (in the case of blocks, the center coordinates of the blocks). As a result, the peripheral light amount drop correction process in the dark part correction can be reflected in each gain value. In this way, each processing for obtaining each image processing correction coefficient reflecting the peripheral light amount drop correction is performed in the development processing unit 116.

  As described above, when the optical aberration correction process of the photographing lens is performed, the aberration correction of the photographing lens is performed in parallel with the image correction process such as the white balance correction process. Further, based on this correction process, correction coefficients and the like in various image processes are changed. Accordingly, it is possible to save the memory amount, maintain the continuous shooting performance and the continuous shooting performance, and improve the image quality by the aberration correction processing.

  In this embodiment, the case of correcting the distortion of the peripheral light amount as an aberration of the photographing lens has been described as an example, but the same processing is performed when correcting other aberrations such as lateral chromatic aberration, axial chromatic aberration, and distortion aberration. By doing so, the same effect can be obtained.

(Second Embodiment)
As in the first embodiment, the present embodiment is a method for performing detection processing and image correction coefficient calculation processing for various types of image processing in parallel with peripheral light amount drop correction. It is characterized in that it is performed within a range that is not affected by the drop in the amount of light.

  FIG. 13 is a diagram illustrating a block configuration of a digital camera according to the second embodiment. Of the block configurations of the present embodiment, those having the same functions as those of the first embodiment are denoted by the same reference numerals. In the present embodiment, a detection condition instruction unit 242 is provided instead of the correction coefficient conversion unit 141 of the first embodiment. The basic functions are the same as the feature amount detection block 130 and the correction coefficient calculation block 131 of the first embodiment, but the feature amount detection block 230 and the correction coefficient that perform processing according to the condition designation of the detection condition instruction unit 242 A calculation block 231 is included.

  Next, the aberration correction processing by the aberration correction unit 115 and the parallel processing of the detection processing and calculation processing by the feature amount detection block 230 and the correction coefficient calculation block 231 will be described, which are features of the present embodiment. In the present embodiment, as in the first embodiment, the aberration correction processing unit passes through the buffer memory 114 in parallel with the detection processing in the feature amount detection block 230 and the calculation processing in the correction coefficient calculation block 231. In 115, peripheral light amount drop correction processing is performed. Thereby, it is possible to improve the shooting performance, such as increasing the continuous shooting interval or increasing the number of continuous shots. However, as in the first embodiment, the captured image input to the feature amount detection block 230 is image data before aberration correction, and therefore still has distortion due to a decrease in peripheral light amount.

  In this embodiment, the detection condition instructing unit 242 defines a range that is greatly affected by the distortion of the peripheral light amount when analyzing the image data captured by the detection unit of each image processing of the feature amount detection block 230.

  Further, the detection condition instruction unit 242 receives the peripheral light amount drop correction data output from the camera control unit 110, and analyzes the gain of the data corresponding to the image height. Here, for example, if a range in which an image height having a gain of 1.2 times or more is affected by the distortion of the peripheral light amount drop, detection including coordinates in the screen corresponding to the image height having a gain of 1.2 times or more is performed. The feature amount detection block 230 is instructed to exclude the position from the detection range.

  FIG. 14 shows an example of a one-screen image in which the influence range is defined. As shown in the figure, assuming that the range from the center coordinates 1404 of the full screen 1401 to the peripheral light amount drop correction gain of less than 1.2 times the image height is an arrow 1405, the block used for the detection processing of each image processing is a thick frame 1403. It is within the range surrounded by.

  Each detection unit of the feature amount detection block 230 is configured to limit the detection processing range in accordance with an instruction from the detection condition instruction unit 242. Therefore, the detection condition instruction unit 242 limits the detection processing of all image processing within this range. Unlike the first embodiment, the correction coefficient calculation block 231 calculates a coefficient based on the detection result from the feature amount detection block 230 without considering any aberration correction processing conditions. By configuring in this way, it is possible to reduce the influence of each image processing due to distortion due to a decrease in peripheral light amount.

  As described above, in the present embodiment, when the optical aberration correction process of the photographing lens is performed, the aberration correction of the photographing lens is performed in parallel with the image correction process such as the white balance correction process. The operation range of the detection process for the correction process is limited to a range where the influence of the aberration correction process is small. Accordingly, it is possible to save the memory amount, maintain the continuous shooting performance and the continuous shooting performance, and improve the image quality by the aberration correction processing. Further, the correction related to the aberration correction process can be performed without complicating the process in the feature amount detection block and the correction coefficient calculation block as compared with the first embodiment.

  In the present embodiment, the detection condition instructing unit 242 limits the detection processing of all image processing to the range shown in FIG. 14, but may limit each processing individually. For example, if face detection is more susceptible to erroneous detection due to aberration than WB detection, the detection range for face detection can be narrower than the WB detection range.

It is a block diagram which shows the structure of the single-lens reflex digital camera in 1st Embodiment. It is a figure showing the gain of a peripheral light amount fall correction | amendment. It is a figure showing the change of the gain of a peripheral light amount fall correction | amendment. It is a figure explaining peripheral light amount fall correction | amendment. It is a figure which shows the arrangement | sequence of each pixel. It is a figure showing the relationship between an image processing block and image height. It is a figure explaining the brightness and contrast correction when an image is dark. It is a figure explaining the gain when an image is dark, and the gain of contrast correction. It is a figure explaining the brightness | luminance and contrast correction | amendment by backlight imaging | photography. It is a figure explaining the brightness and the gain of contrast correction in backlight photography. It is a figure which shows the block of dark part correction | amendment. It is explanatory drawing for calculating | requiring the gain of dark part correction | amendment. It is a block diagram which shows the structure of the single-lens reflex digital camera in 2nd Embodiment. It is a figure which shows the influence range by the distortion of a peripheral light amount fall. It is a figure which shows the block configuration of the conventional digital camera.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 Camera main body 110 Camera control part 115 Aberration correction part 116 Development processing part 130 Feature-value detection block 131 Correction coefficient calculation block

Claims (11)

A first on the basis of the correction coefficient, the first correction means for correcting the image data output from the imaging means to imaging an object image formed through an optical lens for correcting aberration of the optical science lens,
A feature amount detection means for detecting a feature amount from image data output from the imaging means that has not been corrected by the first correction means;
Coefficient calculation means for calculating a second correction coefficient based on the feature quantity detected by the feature quantity detection means;
Second correction means for correcting the image data corrected by the first correction means based on the second correction coefficient;
Anda conversion means for converting the first correction coefficient for the calculation of the detection or the second correction coefficient of the feature quantity,
The feature amount detection unit or the coefficient calculation unit detects the feature amount or calculates the second correction coefficient using the correction data converted by the conversion unit, and the second correction unit performs the conversion. An image processing apparatus for correcting the image data corrected by the first correction unit based on the second correction coefficient obtained by using the correction data. The characteristic amount detecting means and said coefficient calculation means performs calculation of detection and the second correction coefficient of the feature amounts for the white balance correction, the second correction means based on said second correction factor The image processing apparatus according to claim 1, wherein white balance correction is performed on the image data. The performed calculation of detection and the second correction coefficient of the feature, the second correction means the second correction coefficients for the feature quantity detecting means and said coefficient calculating means calculates the brightness and contrast correction The image processing apparatus according to claim 1, wherein brightness and contrast correction of the image data is performed based on the image data. The characteristic amount detecting means and said coefficient calculation means performs the calculation of the feature quantity of detection De及 beauty the second correction coefficient for the brightness correction of the face, the second correction means and the second correction The image processing apparatus according to claim 1, wherein the brightness of the face of the image data is corrected based on a coefficient. The characteristic amount detecting means and said coefficient calculation means performs the calculation of the feature quantity of detection De及 beauty the second correction coefficients for I.EXPOSURE, the second correction means based on the second correction factor The image processing apparatus according to claim 1, wherein dark image correction is performed on the image data. At least one processing of calculating detection and the second correction coefficient of the characteristic amount, to any one of claims 1 to 5, characterized in that in parallel the correction processing by the first correction means The image processing apparatus described. The image processing apparatus according to claim 1, wherein the aberration of the optical lens includes at least one of a peripheral light amount drop, a chromatic aberration of magnification, an axial chromatic aberration, and a distortion aberration. The optical lens in the imaging means are interchangeable, the image processing apparatus according to claim 1, wherein each optical science lens first correction factor is characterized that you have been stored in the storage means. A first on the basis of the correction coefficient, the first correction means for correcting the image data output from the imaging means to imaging an object image formed through an optical lens for correcting aberration of the optical science lens,
Instructing means for instructing a feature amount detection condition in accordance with the first correction coefficient ;
A feature amount detection unit that detects a feature amount from image data output from the imaging unit that is not corrected by the first correction unit based on a detection condition instructed by the instruction unit;
Coefficient calculation means for calculating a second correction coefficient based on the feature quantity detected by the feature quantity detection means;
Second correction means for correcting the image data corrected by the first correction means based on the second correction coefficient calculated by the coefficient calculation means;
An image processing apparatus comprising: An image processing method of an image processing apparatus for correcting image data obtained by an imaging unit that images a subject image formed through an optical lens,
A first correction step of correcting image data output from the imaging means based on a first correction coefficient for correcting aberration of the optical lens;
A feature amount detection step of detecting a feature amount from the image data output from the imaging means that has not been corrected by the first correction step;
A coefficient calculation step of calculating a second correction coefficient based on the feature amount detected by the feature amount detection step;
A second correction step of correcting the image data corrected by the first correction step based on the second correction coefficient;
Has, a conversion step of converting the first correction coefficient for the calculation of the detection or the second correction coefficient of the feature quantity,
The feature amount detection step or the coefficient calculation step detects the feature amount or calculates the second correction coefficient using the correction data converted by the conversion step, and the second correction step performs the conversion. An image processing method for an image processing apparatus, wherein the image data corrected in the first correction step is corrected based on the second correction coefficient obtained by using the corrected data. An image processing method of an image processing apparatus for correcting image data obtained by an imaging unit that images a subject image formed through an optical lens,
A first correction step of correcting image data output from the imaging means based on a first correction coefficient for correcting aberration of the optical lens;
An instruction step of instructing a feature amount detection condition in accordance with the first correction coefficient;
A feature amount detection step of detecting a feature amount from the image data output from the imaging means that has not been corrected by the first correction step based on the detection condition instructed by the instruction step;
A coefficient calculation step of calculating a second correction coefficient based on the feature amount detected by the feature amount detection step;
A second correction step of correcting the image data corrected in the first correction step based on the second correction coefficient calculated in the coefficient calculation step;
An image processing method for an image processing apparatus, comprising:

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