JP5127628B2 - Image processing apparatus and image processing method - Google Patents

Description

  The present invention relates to an image processing apparatus and an image processing method, and more particularly, to an image processing apparatus and an image processing method suitable for use in an imaging apparatus that performs gradation correction on an image captured using an imaging element.

  Conventionally, an image signal output from an image sensor is converted into image data through a process called development, and is used for recording on a recording medium and display on a display device. In this development processing, signal processing corresponding to preset gradation characteristics is performed on the signal output from the image sensor to obtain image data.

  For example, as illustrated in FIG. 11, a plurality of tables (referred to as tone curves) indicating input / output characteristics of image data are prepared. In FIG. 11, the horizontal axis and the vertical axis indicate the luminance values of the input image data and the output image data on the logarithmic axis, respectively. In the example of FIG. 11, three types of tone curves 300 to 302 are prepared, and the gradation characteristics of the input image data are converted according to the selected tone curve. Such gradation characteristic conversion processing is referred to as γ processing. In this example, the gradation characteristics are converted and the data length is also converted.

  For example, the user selects a tone curve that has appropriate image characteristics from the tone curves 300 to 302 according to the output destination of the image data, and performs γ processing on the image data. In the tone curve, for example, a characteristic proportional to the logarithm of the input signal is given to the intermediate luminance region, and the gradation property of the input original image data is not lost as much as possible in the high luminance region and the low luminance region. The compression property is given as follows.

  In recent years, as disclosed in Patent Document 1, a histogram is detected in each region obtained by dividing the screen of a captured image, and an optimum tone characteristic (tone curve) that is processed for the entire screen with reference to the histogram is described. ) Is automatically determined.

  In addition, in Patent Document 1, the sharpness (contrast state) is detected from the image data of each divided region, and the region with high sharpness is recognized as the main subject. In accordance with the magnitude of sharpness, weighting is performed so that the histogram of the main subject region is regarded as important, and then the gradation characteristics are determined.

JP 2003-046778 A

  However, the method described in Patent Document 1 has a problem that the processing result may greatly depend on the frequency characteristics of the image of the subject itself.

  For example, consider a case where the focal position of the imaging optical system is photographed in accordance with one of the plurality of subjects (referred to as a main subject) within the photographing range of the imaging optical system. In this case, there are cases where the image of the main subject portion has few high-frequency components and the image of the subject at a position other than the main subject has many high-frequency components.

  At this time, the image of the subject having a higher frequency component than the image of the main subject has a sharpness value detected from the captured image data of the sharpness of the main subject even when the subject is not focused. May be larger than the value. In such a case, there is a problem that proper histogram detection cannot be performed and γ processing may be performed with inappropriate gradation characteristics.

  On the other hand, it is conceivable that the luminance value is converted for only a part of the area in the photographed screen to obtain appropriate image data. In this case, if the luminance value of the target area is corrected using the gradation characteristics uniformly given to the entire screen, the luminance value is close to the main subject and has a small correlation with the main subject other than the main subject. Similar gradation characteristics are given, and an unnatural image may be output.

  As an example, let us consider a case where a plurality of persons 310 to 312 are in the shooting range as subjects, as in the subject shown in FIG. In the example of FIG. 12, it is assumed that the main subject is only the person 310 and the shooting distance is the shortest among the persons 310 to 312. Further, it is assumed that the persons 311 and 312 other than the main subject have different shooting distances from the main subject and are out of focus.

  In such a case as shown in FIG. 12, according to the gradation characteristic correction method of Patent Document 1, an appropriate gradation characteristic is given to the image of the person 310 as the main subject, and a desirable image quality can be achieved. . On the other hand, when the luminance value of the image of the person 311 and / or 312 that is farther away than the main subject is close to the luminance value of the image of the person 310 that is the main subject, the person 310 is compared with the person 311 and / or 312. The same gradation characteristics are given. In this case, the correction of the luminance value for the image of the person 311 and / or 312 is unnaturally performed on the background image, which may cause an unsightly shooting result.

  Accordingly, an object of the present invention is to provide an image processing apparatus and an image processing method capable of correcting gradation characteristics so as to obtain a preferable photographing result.

The present invention, in order to solve the problems described above, the row Cormorant face detecting means face detection based on the image signal output from the imaging device, corresponding to the face area of said detected image signal by said face detecting means a defocus amount obtaining means for obtaining a correction amount obtaining means for obtaining a correction amount against a range, a defocus amount in each of the plurality of focus detection areas in the photographing screen, is obtained by the defocus amount acquiring means based on said defocus amount, and the first coefficient acquisition means acquire the first coefficient for weighting with respect to the correction amount obtained by the correction amount acquisition unit, for a range corresponding to the face area, and characterized in that it has an image characteristic correction means for correcting the image characteristics by using the correction amount weighted by the first coefficient based on the defocus amount of the focus detection area corresponding to the range That is an image processing apparatus.

Further, the present invention, the correction amount against the range corresponding to the face region of the rows Cormorant face detecting step face detection based on the image signal output from the imaging device, the image signal detected by the face detection step a correction amount acquisition step of acquiring, based on the defocus amount obtained by the defocus amount acquisition step of acquiring a defocus amount, in the defocus amount acquisition step each of the plurality of focus detection areas in the photographing screen the focus of the first coefficient acquisition step get the first coefficient for weighting with respect to the correction amount obtained by the correction amount acquisition step, for a range corresponding to the face region, corresponding to the range to have an image characteristic correction step of correcting the image characteristics by using the correction amount weighted by the first coefficient based on the defocus amount detection area The image processing method according to claim.

  Since the present invention has the above-described configuration, the gradation characteristics can be corrected so as to obtain a preferable photographing result.

<Embodiment>
Embodiments of the present invention will be described below with reference to the drawings. First, an image sensor applicable to the embodiment of the present invention will be described. An imaging device applicable to the embodiment of the present invention is composed of, for example, a CMOS image sensor, and pixels are arranged in a matrix. A color filter that performs color separation of incident light is arranged for each pixel.

In this embodiment, a Bayer array is adopted as the color filter array. That is, as illustrated in FIG. 1, pixels G ₁ and G ₂ having spectral sensitivity with respect to green (G) are arranged on two diagonal pixels with 4 pixels of 2 rows × 2 columns as a unit. In addition, pixels R and B having spectral sensitivity to red (R) and blue (B) are arranged on the other two pixels, respectively.

  An imaging optical system including an imaging element will be schematically described with reference to FIG. FIG. 2A shows a plan view of an example of pixels of 2 rows × 2 columns by a Bayer array. FIG. 2B is a cross-sectional view of an example of the imaging optical system, taken along plane AA in FIG.

The photodiode PD is a photoelectric conversion element of a CMOS image sensor and constitutes a pixel. The contact layer CL is a wiring layer that forms signal lines for transmitting various signals in the CMOS image sensor. For each pixel, a red color filter CF _R , a green color filter CF _G and a blue color filter CF _B are arranged in a Bayer array as shown in FIG. On-chip microlenses ML are arranged on the forefront of each pixel.

Light from the subject is incident on the on-chip microlens ML via an optical photographing lens TL (Taking Lens) and is condensed. Condensed light is incident on the photodiode PD, for example, the extracted red wavelength components by the color filter CF _R. The photodiode PD converts incident light into electric charge by photoelectric conversion.

  Here, the on-chip microlens ML and the photodiode PD of the imaging pixel are configured to capture the light beam that has passed through the optical photographing lens TL as effectively as possible. In other words, the exit pupil EP (Exit Pupil) of the optical photographing lens TL and the photodiode PD are conjugated with each other by the on-chip microlens ML, and the effective area of the photodiode PD is designed to be large.

The pixels corresponding to the color filters CF _R , CF _G, and CF _B (hereinafter referred to as R pixel, G pixel, and B pixel, respectively) have the same structure. Accordingly, the exit pupil EP corresponding to each of the R, G, and B pixels for imaging has a large diameter, and light from the subject can be efficiently taken into the photodiode PD, and S of the imaging signal output from the imaging element can be obtained. / N is improved.

  Focus detection pixels for performing focus detection by the pupil division phase difference method are arranged between the Bayer arrays. More specifically, among the 2 rows × 2 columns of pixels constituting the Bayer array, the G pixel is left as an imaging pixel, and the R pixel and the B pixel are replaced with focus detection pixels.

  When obtaining an image signal for recording or display, the main component of luminance information is acquired by G pixels. Since human image recognition characteristics are sensitive to luminance information, if this G pixel is missing, image quality degradation is likely to be perceived. On the other hand, the R pixel or the B pixel mainly acquires color information (color difference information). Here, human image recognition characteristics are less sensitive to color information than luminance information. For this reason, it is difficult for the R pixel and B pixel for obtaining the color information to recognize the image quality deterioration even if some loss occurs.

  With reference to FIG. 3, an imaging optical system including an imaging element according to a focus detection pixel will be schematically described. FIG. 3A shows a plan view of an example of pixels of 2 rows × 2 columns including focus detection pixels. FIG. 3B is a cross-sectional view of an example of the imaging optical system taken along plane AA in FIG. In FIG. 3B, the on-chip microlens ML and the photodiode PD have the same structure as that shown in FIG.

In FIG. 3A, a pixel S _HA and a pixel S _HB are pixels for performing focus detection. Hereinafter, the pixel S _HA and the pixel S _HB are collectively referred to as a focus detection pixel. In FIG. 3A, the filled portions in the pixels S _HA and S _HB are openings of the wiring layer CL. That is, the light irradiated to the focus detection pixels is incident on the photodiode PD through the opening of the wiring layer CL. The signal due to the focus detection pixels, is not used for image generation, to the pixel S _HA and the pixel S _HB, filter CF _W by the transparent film is arranged.

In the example of FIG. 3, the opening _{OP HA} corresponding to the pixel _{S HA,} and, the opening _{OP HB} corresponding to the pixel _{S HB,} is provided offset in one direction from the center line of the on-chip microlens ML . Thereby, pupil division by an image sensor is performed.

Specifically, since the opening OP _HA corresponding to the pixel S _HA is biased to the right side in FIG. 3, the light beam that has passed through the left exit pupil EP _HA of the optical photographing lens TL is received. Similarly, since the opening OP _HB corresponding to the pixel S _HB is biased to the left in FIG. 3, it receives the light beam that has passed through the right exit pupil EP _HB of the optical photographing lens TL.

Pixels _SHA are regularly arranged in the horizontal direction, and a subject image acquired by these pixel groups is defined as an image A. Similarly, the pixels _SHB are regularly arranged in the horizontal direction, and a subject image acquired by these pixel groups is defined as an image B. By detecting the relative position between the image A and the image B, the amount of defocus (defocus amount) of the subject image can be detected.

The pixels S _HA and S _HB , which are focus detection pixels for performing pupil division in the horizontal direction of the optical photographing lens TL, are regularly arranged on the entire screen of the image sensor as illustrated in FIG. Be placed. Each focus detection pixel is set with a focus detection region for performing focus detection, as illustrated by a frame line in FIG.

Note that, in the pixels S _HA and S _HB described above, the openings OP _HA and OP _HB are provided in the vertical direction. Therefore, when the pixels S _HA and S _HB are arranged in the horizontal direction, it is possible to detect a focus on a subject having a luminance distribution in the horizontal direction of the photographing screen, for example, a vertical line. In order to perform focus detection on a subject such as a horizontal line having a luminance distribution in the vertical direction, a pixel in which the openings _SHA and _SHB are rotated by 90 degrees and the opening is provided in the horizontal direction is used. By constructing the focus detection pixels in which the openings are provided in the vertical direction and the focus detection pixels in which the openings are provided in the horizontal direction, the vertical luminance distribution and the horizontal luminance are provided. It can correspond to the distribution.

  FIG. 5 is a functional block diagram showing functions of an example of an imaging apparatus applicable to the embodiment of the present invention. Note that, in FIG. 5, among the functions of the imaging apparatus, a shallow portion related to the present embodiment is omitted.

  The optical photographing lens 101 includes a plurality of lenses, and includes an aperture mechanism, a focus mechanism, a zoom mechanism, and a drive unit that drives these mechanisms. The subject image condensed by the optical photographing lens 101 is formed on the image sensor 102. As described with reference to FIGS. 1 to 4, the image sensor 102 has color filters in a Bayer array, and focus detection pixels are regularly arrayed on the entire screen. The image sensor 102 photoelectrically converts the imaged light and outputs it as an analog image signal. This analog signal is converted into a digital signal by the A / D converter 103.

  On the other hand, the output of the image sensor 102 is supplied to the focus amount detection unit 110. A focus amount detection unit 110 serving as a focus amount acquisition unit detects the above-described defocus amount using a signal of a focus detection pixel in the output of the image sensor 102. Here, the detected defocus amount is defined as a focus amount as an evaluation value indicating a focus degree in the imaging optical system. The focus amount detection unit 110 calculates and stores a focus amount, that is, a defocus amount, for each focus detection pixel of the image sensor 102.

  The imaging information acquisition unit 150 acquires focal length information 151, aperture information 152, and focal position information 153 from the optical photographing lens 101. The focal length information 151 indicates the focal length of the optical photographing lens 101 at the time of photographing. Aperture information 152 indicates a set value of an aperture (not shown) provided in the optical photographing lens 101. The focal position information 153 indicates the distance from the image sensor 102 of the focused subject.

  The output of the A / D conversion unit 103 is supplied to the focus detection pixel interpolation unit 104. The focus detection pixel does not output image data as a display or recording image. For this reason, the focus detection pixel interpolation unit 104 uses the actual image pixels around the focus detection pixel to process the defective pixel interpolation at the position where the focus detection pixels are arranged in the screen of the image sensor 102. Interpolation processing is performed in the same manner as described above.

  The image data output from the focus detection pixel interpolation unit 104 is subjected to image processing generally performed by a digital camera or the like, such as γ processing 160, sharpness processing 161, and color processing 162, in the development processing unit 105. At this time, as described with reference to FIG. 11 in the background art, the γ processing 160 performs γ processing using a tone curve selected from a plurality of predetermined tone curves.

  The image data output from the development processing unit 105 is supplied to the tone characteristic correction unit 115 and also to the face detection unit 106. The face detection unit 106 serving as a face detection unit performs face detection processing 171 on the supplied image data, and for the face detected from the image data, the position and range in the screen based on the image data, and the face image And the average value of the luminances. Face position information 172 and face range information 173 indicating the position and range of the face, and face luminance information 174 indicating the average value of the luminance of the face image are respectively supplied to the correction amount calculation unit 107. The face position information 172 and the face range information 173 are also supplied to the gradation characteristic correction unit 115, respectively.

  The face position information 172, face range information 173, and face luminance information 174 output from the face detection unit 106 will be described more specifically with reference to FIG. As the face position information 172, coordinate information of the center position 602 in the face whose face is detected is used. The face range information 173 uses a range 601 (hereinafter referred to as a face range 601) including pixels having a luminance value in a predetermined range with respect to the luminance value of the center position of the face detected. For example, when the maximum luminance value is 255, a range having a luminance value of ± 20 with respect to the luminance value at the center position of the face is set as the face range 601. The face luminance information 174 uses the average luminance value of the pixels within the range indicated by the face range information 173.

  A known face detection technique can be used for face detection in the present embodiment. As a known face detection technique, a method based on learning using a neural network or the like, template matching is used to search a part having a characteristic shape of eyes, nose, mouth, etc. from an image, and if the similarity is high, it is regarded as a face There are methods. In addition, many other methods have been proposed, such as a method that detects image feature amounts such as skin color and eye shape and uses statistical analysis. In general, a plurality of these methods are combined to improve the accuracy of face detection. Specific examples include a face detection method using wavelet transform and image feature amount described in JP-A-2002-251380.

  The face position information 172, face range information 173, and face luminance information 174 output from the face detection unit 106 are supplied to the correction amount calculation unit 107. Based on the supplied information, the correction amount calculation unit 107 as a correction amount acquisition unit limits the range only to the face image in the screen based on the image data based on the output of the image sensor 102 and its peripheral position, A correction amount for correcting the gradation characteristics within the range is determined and output.

  7A and 7B show examples of tables for determining the correction amount in the correction amount calculation unit 107. FIG. In this example, the gain for the face luminance information 174 is determined as the correction amount. According to these tables, the luminance value is corrected by multiplying the gradation characteristic by the correction amount (gain) corresponding to the luminance value. Here, it is assumed that the luminance value is expressed by 8 bits and the maximum value is 255.

  For example, the table of FIG. 7A shows that when the face luminance information 174 is an average luminance value of 170 or less, the face brightness is multiplied by a positive gain. Further, when the face luminance information 174 is a luminance average value of value 80, the maximum gain is multiplied. When the average luminance value is smaller than the value 80 or larger than the value 80, a positive value is set so as not to perform excessive correction. This means that the gain value is gradually reduced.

  FIG. 7B shows an example of switching the gain as the correction amount in accordance with the detected position with respect to the face. As an example, assume that the first positive gain is determined as the correction amount for the detected face range 601 as shown in FIG. 6 described above. For example, the first positive gain is gradually decreased as the distance from the face range 601 increases to the periphery, for example, every predetermined pixel.

  This will be described more specifically with reference to FIG. FIG. 8 corresponds to FIG. 6 described above. For example, a range 501 in FIG. 8 is a range indicated by the face range information 173 and corresponds to the face range 601 in FIG. First, for the range 501, the first positive gain indicated by the table 201 in FIG. 7B is determined as the correction amount. For a range 502 of several pixels outside the range 501 (for example, two pixels), a second positive gain smaller than the first positive gain shown in the table 202 in FIG. decide. Further, a third positive gain smaller than the second positive gain shown in the table 203 in FIG. 7B is corrected for a range 503 of several pixels outside the range 502 (for example, two pixels). Determine as quantity.

  In this way, the gradation characteristics change unnaturally at the boundary between the face image whose gradation characteristics are to be corrected and the surrounding area by gradually reducing the gain as the correction amount as the distance from the correction target range increases. To be suppressed.

  A correction amount weighting calculation unit 114 serving as a weighting unit calculates a focus degree evaluation value and a shooting distance evaluation value described below as weighting coefficients for the correction amount output from the correction amount calculation unit 107, and A correction amount used in the gradation characteristic correction unit 115 is calculated.

  First, the focus degree evaluation value will be described. The focus amount detection unit 110 refers to the focus degree evaluation value table 111 as the first coefficient acquisition unit based on the detected focus amount of each focus detection region, and focuses for each focus detection region. The degree evaluation value is obtained. In this embodiment, the smaller the in-focus amount, that is, the defocus amount output from the focus detection pixel, the higher the degree of focus and the focus detection area set for the focus detection pixel is photographed. It is assumed that the area is

  In the present embodiment, a table is provided that performs weighting that places importance on subjects with a higher degree of focus. FIG. 9 shows an example of such a focus degree evaluation value table 111. In the example of FIG. 9, it is defined that the range of the defocus amount from 0 to a predetermined value (for example, 10) is high in focus, and in the range of the defocus amount where the focus is high, the focus degree evaluation value is 1 .0. On the other hand, for the defocus amount exceeding the predetermined value, a characteristic that decreases as the defocus amount increases is given to the focus degree evaluation value. With reference to this focus degree evaluation value table 111 for each focus detection area, a focus degree evaluation value for each focus detection area is obtained.

Note that the maximum defocus amount (10 in the above example) with the in-focus evaluation value of 1.0 is set to the depth of field of the captured image using the aperture information 152 and the focal length information 151. It can be changed accordingly.

  Next, the shooting distance evaluation value will be described. Based on the focus amount evaluation value obtained by referring to the focus degree evaluation value table 111 based on the detection result of the focus amount detection unit 110 and the focus position information 153 extracted by the imaging information acquisition unit 150, the focus detection region Each time, shooting distance information indicating the distance to the subject is acquired. The shooting distance evaluation value is obtained by referring to the shooting distance evaluation value table 112 based on the shooting distance information. The shooting distance evaluation value is obtained for each focus detection area. The imaging information acquisition unit 150 and the focus amount detection unit 110 form a distance acquisition unit.

  In the present embodiment, a table is provided that performs weighting that places importance on subjects with a shorter shooting distance. FIG. 10 shows an example of the shooting distance evaluation value table 112 as such second coefficient acquisition means. In the example of FIG. 10, it is defined that the importance of a subject photographed in a range from a shortest photographing distance (for example, 0 m) of a lens used for photographing to a predetermined distance (for example, 12 m) is high, and a photographing distance evaluation value in this range. Is 1.0. On the other hand, for the shooting distance exceeding the predetermined distance, the shooting distance evaluation value is given a characteristic that decreases rapidly as the shooting distance increases. FIG. 10 shows an example, and this characteristic varies depending on the focal length of the lens. For example, the larger the focal length of the lens, the longer the shooting distance at which the weight starts to decrease from 1.0. In addition, since the focal length of a lens having a longer focal length is steeper, the weighting gradient becomes steeper.

  In addition, regarding the shooting distance, the focal length information 151 indicating the focal length of the lens may be further considered. In this case, it is conceivable that characteristics corresponding to the focal length information 151 are given to the shooting distance evaluation value table 112.

  The correction amount weighting calculation unit 114 performs an operation on the correction amount for correcting the gradation characteristics supplied from the correction amount calculation unit 107 using the focus degree evaluation value and the shooting distance evaluation value as weighting coefficients, respectively. Thus, the correction amount is weighted with respect to the defocus amount and the shooting distance.

The correction amount weighting calculation unit 114 calculates the corrected gain G in accordance with the following equation (1), for example. In equation (1), the value a is a value obtained by multiplying the focus degree evaluation value and the shooting distance evaluation value, and takes a value of 0 ≦ a ≦ 1. The value g is a correction amount (gain) obtained by referring to the table in the correction amount calculation unit 107, and takes a value of g ≧ 1. As can be seen from this equation (1), the value a controls the gain obtained by the correction amount calculation unit 107 between 1 and the value g.
G = 1 + a (g-1) (1)

  The gain G that is the correction amount of the gradation characteristic weighted by the correction amount weighting calculation unit 114 is supplied to the gradation characteristic correction unit 115. Based on the gain G, the gradation characteristic correction unit 115 performs image characteristic correction processing on the image data supplied from the development processing unit 105. More specifically, the gradation characteristic correcting unit 115 multiplies the gain G by the gain characteristic, and based on the gradation characteristic multiplied by the gain G, the image data supplied from the development processing unit 105 is obtained. Convert luminance values. At this time, based on the face position information 172 and the face range information 173, the luminance value conversion process is performed for each focus detection area corresponding to the range indicated by the face range information 173 and the surrounding predetermined range in the image data. .

  The image data whose gradation characteristics have been converted by the gradation characteristic correction unit 115 is output from the output unit 116, and is displayed on a display unit (not shown) or recorded on a recording medium.

  As described above, according to the embodiment of the present invention, face detection is performed on captured image data, and a correction amount is set for correcting gradation characteristics for the detected face range. To do. The correction amount is weighted according to the degree of focus and the shooting distance to the subject. For this reason, even when a plurality of persons are photographed in one image data, a process that corrects the brightest gradation characteristic with respect to the brightness of the face in the place where the photographing lens is focused is performed. An image can be output.

It is a figure for demonstrating a Bayer arrangement. It is a figure for demonstrating the imaging optical system containing an image pick-up element. It is a figure for demonstrating the imaging optical system containing the image pick-up element which concerns on the pixel for focus detection. It is a figure which shows arrangement | positioning of an example of the pixel for focus detection. It is a functional block diagram which shows the function of an example of the imaging device applicable to embodiment of this invention. It is a figure for demonstrating the information output from a face detection part. It is a figure which shows the example of the table which determines the correction amount in a correction amount output part. It is a figure for demonstrating switching the gain as a correction amount according to the position with respect to the detected face. It is a figure which shows an example of the focus degree evaluation value table which performs weighting which attaches importance to a subject with a high focus degree. It is a figure which shows an example of the shooting distance evaluation value table which weights so that it attaches importance to a subject with a short shooting distance. It is a figure for demonstrating a tone curve. It is a figure for demonstrating that a malfunction may generate | occur | produce when a several person is image | photographed.

Explanation of symbols

DESCRIPTION OF SYMBOLS 102 Image pick-up element 105 Development processing part 106 Face detection part 107 Correction amount calculation part 110 Focus amount detection part 111 Focus degree evaluation value table 112 Shooting distance evaluation value table 114 Correction amount weighting calculation part 115 Gradation characteristic correction part 150 Imaging information Acquisition department

Claims (8)

A row Cormorant face detecting means face detection based on the image signal output from the imaging element,
A correction amount obtaining means for obtaining a correction amount against a range corresponding to the face area of said detected image signal by said face detecting means,
Defocus amount acquisition means for acquiring the defocus amount in each of a plurality of focus detection areas in the shooting screen ;
Based on the defocus amount obtained by the defocus amount acquiring means, a first coefficient acquisition means acquire the first coefficient for weighting with respect to the correction amount obtained by the correction amount acquisition unit,
Image characteristic correction for correcting an image characteristic for a range corresponding to the face area using the correction amount weighted by the first coefficient based on the defocus amount of the focus detection area corresponding to the range And an image processing apparatus. Distance acquisition means for acquiring, for each focus detection area, shooting distance information indicating a distance to a subject imaged by the imaging element;
It said distance based on the object distance information obtained by the obtaining means further comprises a second coefficient obtaining means get the second coefficient for weighting with respect to the correction amount obtained by the correction amount acquisition unit,
The image characteristic correcting unit weights a range corresponding to the face area with the first coefficient based on the defocus amount of the focus detection area corresponding to the range and the second coefficient based on shooting distance information. The image processing apparatus according to claim 1, wherein the correction is performed using the corrected amount . The correction amount acquisition unit, a correction amount for the range around the range corresponding to the face area, claim 1, characterized in that to obtain a smaller value Ri by hand as the distance from the range corresponding to the face area or The image processing apparatus according to claim 2. The image processing apparatus according to claim 1, wherein the image characteristic correction unit performs the correction using a gradation characteristic as the image characteristic. The image sensor has a plurality of focus detection pixels for focus detection by a pupil division phase difference method,
The focus detection area, the image processing apparatus according to any one of claims 1 to 4, characterized in <br/> that corresponds to the position of the focus detection pixel. 6. The correction amount acquisition unit according to claim 1, wherein the correction amount acquisition unit acquires a correction amount for a range corresponding to the face area based on luminance of the range corresponding to the face area. Image processing apparatus. The correction amount acquisition unit acquires a larger value as a correction amount for the range corresponding to the face area as the luminance of the range corresponding to the face area is closer to a predetermined value. Image processing apparatus. A row Cormorant face detecting step face detection based on the image signal output from the imaging element,
A correction amount acquisition step of acquiring a correction amount against a range corresponding to the face region of the image signal detected by the face detecting step,
A defocus amount acquisition step of acquiring a defocus amount in each of a plurality of focus detection areas in the shooting screen ;
Based on the defocus amount obtained by the defocus amount acquisition step, a first coefficient acquisition step get the first coefficient for weighting with respect to the correction amount obtained by the correction amount acquisition step,
Image characteristic correction for correcting an image characteristic for a range corresponding to the face area using the correction amount weighted by the first coefficient based on the defocus amount of the focus detection area corresponding to the range And an image processing method.

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