JP2009303111A - Image processing apparatus and method, and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To suitably correct contract in an image especially including a face. <P>SOLUTION: A face detection part 59 detects a face from an image acquired by photography. A face luminance calculation part 60 calculates the average luminance of the face. A gradation curve calculation part 61 sets the maximum luminance which can be obtained in the image, an optimum degree and the average luminance of the face as fixed points and calculates a gradation curve for changing gradation characteristics on the high-light side and shadow side of the image based on the fixed points. A gradation processing part 53 performs gradation processing using the calculated gradation curve. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to an image processing apparatus and method for correcting the gradation of an image acquired by photographing, and a program for causing a computer to execute the image processing method.

  In a photographing apparatus such as a digital camera, image quality is improved by performing image processing for correcting image quality such as γ processing, gradation processing, color correction processing, sharpness processing, and noise reduction processing on an acquired image. Improvements are being made. For example, a technique has been proposed in which the gradation characteristics of an image are changed based on camera photometric values, photometric contrast, flash emission information, camera exposure conditions, and the like (see Patent Document 1). For an image including a person, it is desirable to correct the face appropriately. Therefore, by changing the γ of the image, based on the technique of making the brightness of the face appropriate and the brightness of the background appropriate (see Patent Document 2), the brightness of the face and the brightness of the entire image, Appropriate exposure based on the brightness of the face by appropriately adjusting the brightness of the face and detecting a face from the image acquired by the technique (see Patent Document 3) and pre-shooting that prevents background whitening Has been proposed (see Patent Document 4).

On the other hand, a digital camera capable of automatically setting the sensitivity at the time of shooting has been proposed. In such a digital camera, the brightness of the shooting environment is calculated from the exposure value (EV value), and shooting is performed with the ISO sensitivity automatically set according to the exposure value. If such a digital camera is used, the photographer can perform photographing with an appropriate ISO sensitivity corresponding to the brightness of the photographing environment without setting the ISO sensitivity by himself.
JP 2003-234955 A JP 2007-74328 A JP 2007-124604 A JP 2007-201979 A

  As described above, in a digital camera that automatically sets the sensitivity, for example, when shooting is performed without using a flash in a dark shooting environment where the exposure value is 3 EV or less, the ISO sensitivity is increased to 1600 or higher and the sensitivity is increased. To shoot. When performing such high-sensitivity shooting, light contrast cannot be obtained as in a bright shooting environment, so that an image with low overall contrast is acquired. However, when gradation processing is applied to an image with low contrast using a gradation curve that is fixed in advance, the overall image becomes hard and the image looks sharp. The face contrast is too high.

  The present invention has been made in view of the above circumstances, and an object of the present invention is to make it possible to appropriately correct the contrast particularly for an image including a face.

An image processing apparatus according to the present invention includes a face detection unit that detects a face from an image acquired by photographing,
A gradation curve calculating means for calculating a gradation curve for changing a gradation characteristic on a highlight side and a shadow side with reference to the fixed point of the image as a fixed point near the detected luminance of the face;
And image processing means for generating a processed image by performing image quality correction processing including gradation processing using the gradation curve on the image.

  The “near face brightness” may be the brightness of one pixel specified in the detected face, and represents the detected face such as the average brightness or intermediate brightness of the face area including the detected face. It may be brightness. In addition to the value of the face brightness or the average brightness itself, it may include some errors.

  In the image processing apparatus according to the present invention, when the image quality correction process includes a brightness correction process, the gradation curve calculation unit performs gradation using the vicinity of the brightness of the face after the brightness correction as a fixed point. It may be a means for calculating a curve.

In the image processing apparatus according to the present invention, when the image quality correction processing includes γ processing, the gradation curve calculating means calculates a gradation curve with the luminance vicinity of the face after the γ processing as a fixed point. It is good also as a means to do.

  Further, in the image processing apparatus according to the present invention, when the image is acquired by low-luminance shooting, the gradation curve calculation unit is used to make the highlight side harder than the fixed point, and from the fixed point. Alternatively, a means for calculating an S-shaped gradation curve for softening the shadow side may be used.

  “Low luminance shooting” is shooting in which the brightness of the shooting environment is an exposure value of 5 EV or less, preferably 3 EV or less. Note that when ISO sensitivity is set automatically, the shooting is performed so that the ISO sensitivity is 1600 or more.

  In the image processing apparatus according to the present invention, when the image quality correction process includes a color correction process, the image processing unit performs the color correction process so as to lower the saturation of the image after the gradation process. It may be a means.

  In the image processing apparatus according to the present invention, when the image quality correction process includes a noise reduction process, the image processing unit performs the noise reduction process to lower the noise of the image after the gradation process. It may be a means.

The image processing method according to the present invention detects a face from an image acquired by photographing,
A gradation curve that changes the gradation characteristics on the highlight side and the shadow side based on the fixed point of the image as a fixed point in the vicinity of the detected luminance of the face is calculated,
A processed image is generated by performing an image quality correction process including a gradation process using the gradation curve on the image.

  The image processing method according to the present invention may be provided as a program for causing a computer to execute the image processing method.

  According to the present invention, a face is detected from an image acquired by photographing, and the gradation characteristics on the highlight side and the shadow side of the image are changed with the detected luminance near the fixed point as a fixed point. Since the gradation curve to be calculated is calculated and the image quality correction process including the gradation process using the gradation curve is performed on the image, the brightness of the face is not changed by the gradation process. For this reason, the background portion other than the face can have an appropriate contrast according to the gradation curve while maintaining the brightness of the face.

  In addition, when the image quality correction process includes a brightness correction process, it is preferable to maintain a corrected face brightness by calculating a gradation curve with the vicinity of the brightness of the face after the brightness correction as a fixed point. The background portion other than the face can have an appropriate contrast according to the gradation curve.

  In addition, when the image quality correction processing includes γ processing, a face that has been corrected by γ processing in a γ-processed image is preferably calculated by calculating a tone curve with the luminance vicinity of the face after γ processing as a fixed point. The background portion other than the face can have an appropriate contrast according to the gradation curve while maintaining the brightness of the image.

  Further, when the image is taken with low brightness, the brightness of the face is calculated by calculating an S-shaped gradation curve that makes the highlight side harder than the fixed point and softer the shadow side than the fixed point. The background portion other than the face can have an appropriate contrast with sharpness corresponding to the gradation curve.

  Note that when such gradation processing is performed, the saturation of the image is enhanced, although the contrast is increased. For this reason, when the image quality correction processing includes color correction processing, the saturation of the processed image may be made appropriate by performing color correction processing to lower the saturation of the image after the gradation processing. it can.

  Further, when such gradation processing is performed, although the contrast is increased, noise included in the image is emphasized. For this reason, when the image quality correction process includes a noise reduction process, a processed image with reduced noise can be obtained by performing the noise reduction process to lower the noise after the gradation process.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. 1 and 2 are views showing an external appearance of a digital camera 1 to which an image processing apparatus according to an embodiment of the present invention is applied. As shown in FIGS. 1 and 2, a release button 2, a power button 3, and a zoom lever 4 are provided on the top of the digital camera 1.

  The release button 2 has a structure in which two types of operations can be instructed by pressing in two steps. For example, in shooting using an automatic exposure adjustment function (AE: Auto Exposure) and an automatic focus adjustment function (AF: Auto Focus), the digital camera 1 performs a first pressing operation (half-pressing) in which the release button 2 is lightly pressed. (Also called exposure), preparation for shooting such as exposure adjustment and focusing is performed. In this state, when a second pressing operation (also referred to as full pressing) in which the release button 2 is strongly pressed is performed, the digital camera 1 starts exposure and records image data for one screen obtained by the exposure. Record on media.

  On the back of the digital camera 1, a monitor 5 such as a liquid crystal, a mode dial 6 used for setting a shooting mode, and various operation buttons 8 are provided. In the present embodiment, it is possible to set a shooting mode for shooting and a playback mode for playing back an image recorded on a recording medium on the monitor 5.

  Next, the internal configuration of the digital camera 1 will be described. FIG. 3 is a schematic block diagram showing an internal configuration of a digital camera to which the image processing apparatus according to the embodiment of the present invention is applied. As shown in FIG. 3, the digital camera 1 to which the image processing apparatus according to the present embodiment is applied has an imaging unit 10.

  The imaging unit 10 includes a photographing lens 12 including a focus lens and a zoom lens. The photographic lens 12 includes a plurality of functional lenses such as a focus lens for focusing on a subject and a zoom lens for realizing a zoom function. The lens driving unit 13 is a small motor such as a stepping motor, and adjusts the position of each functional lens so that the distance from the CCD 18 to each functional lens is a suitable distance for the purpose.

  The diaphragm 14 includes a plurality of diaphragm blades. The aperture drive unit 15 is a small motor such as a stepping motor, and adjusts the position of the aperture blade so that the aperture size of the aperture becomes a size suitable for the purpose according to the aperture value data output from the AE processing unit 29. .

  The shutter 16 is a mechanical shutter and is driven by a shutter driving unit 17. The shutter drive unit 17 controls the opening and closing of the shutter 16 according to a signal generated by pressing the release button and the shutter speed data output from the AE processing unit 29.

  Behind the shutter 16 is a CCD 18 which is an image sensor. The CCD 18 has a photoelectric surface in which a large number of light receiving elements are two-dimensionally arranged, and subject light that has passed through an optical system such as the photographing lens 12 forms an image on the photoelectric surface and is subjected to photoelectric conversion. In front of the photocathode, a microlens array for condensing light on each pixel and a color filter array in which filters of R, G, and B colors are regularly arranged are arranged. The CCD 18 outputs the charge accumulated for each pixel as a serial analog photographing signal line by line in synchronization with the vertical synchronization signal and horizontal synchronization signal supplied from the CCD control unit 19. The time for accumulating charges in each pixel, that is, the exposure time, is determined by an electronic shutter drive signal given from the CCD controller 19. The gain of the CCD 18 is adjusted by the CCD control unit 19 so that an analog imaging signal having a predetermined size can be obtained.

  The analog photographing signal read from the CCD 18 is input to an analog front end (AFE) 20. The AFE 20 includes a correlated double sampling circuit (CDS) that removes noise from the analog signal, an auto gain controller (AGC) that adjusts the gain of the analog signal, and an A / D converter (ADC) that converts the analog signal into a digital signal. It consists of. The image data converted into the digital signal is CCD-RAW data having R, G, and B density values for each pixel.

  Note that the AGC adjusts the gain of the analog signal by a gain according to the ISO sensitivity data output from the AE processing unit 29 as will be described later.

  The timing generator 21 generates a timing signal. By supplying this timing signal to the shutter drive unit 17, the CCD control unit 19, and the AFE 20, the release button is operated, the shutter 16 is opened and closed, and the charge from the CCD 18 is supplied. And the processing of the AFE 20 are synchronized.

  In addition, the digital camera 1 has a flash 24 that emits light when necessary during photographing.

  The digital camera 1 also has an image input controller 25 that transfers the image data output from the AFE 20 to another processing unit via the data bus 41, and a frame memory 26 that temporarily stores the image data transferred from the image input controller 25. Is provided.

  The frame memory 26 is a working memory used when performing various processes described later on image data. For example, an SDRAM (Synchronous Dynamic Random Access Memory) that performs data transfer in synchronization with a bus clock signal having a constant period. Is used.

  The display control unit 27 displays the image data stored in the frame memory 26 on the monitor 5 as a through image, or displays the image stored on the recording medium 34 on the monitor 5 in the reproduction mode. is there.

  The AF processing unit 28 and the AE processing unit 29 determine shooting conditions based on the pre-image. The pre-image is an image represented by image data stored in the frame memory 26 as a result of the CPU 40 that has detected a half-press signal generated when the release button 2 is half-pressed causing the CCD 18 to perform pre-photographing. It is.

  The AF processing unit 28 detects the focal position based on the pre-image and outputs focus driving amount data (AF processing). As a focus position detection method, for example, a passive method that detects a focus position using a feature that the contrast of an image is high when a desired subject is in focus can be considered.

  The AE processing unit 29 measures the subject brightness based on the pre-image, calculates the aperture value, shutter speed and ISO sensitivity from the exposure value based on the measured subject brightness, and obtains aperture value data (Av value) and shutter speed data ( Tv value) and ISO sensitivity data (Sv value) are output as exposure setting values (AE process). Further, the AE processing unit 29 outputs the exposure value to the image processing unit 31.

  The AWB processing unit 30 automatically adjusts the white balance at the time of shooting (AWB processing).

  The image processing unit 31 performs image quality correction processing such as γ processing, gradation processing, sharpness correction processing, color correction processing, and noise reduction processing on the image data of the main image, and each pixel has a RGB signal value. Thus, the interpolation processing for interpolating the pixel value of each pixel, and the CCD-RAW data are converted into YC data composed of Y data that is a luminance signal, Cb data that is a blue color difference signal, and Cr data that is a red color difference signal. YC processing is performed. The main image is an image that is captured from the CCD 18 by main shooting executed when the release button is fully pressed and is represented by image data stored in the frame memory 26 via the AFE 20 and the image input controller 25. .

  Here, the image quality correction process may be performed after the interpolation process or may be performed before the interpolation process. In the present embodiment, description will be made assuming that image quality correction processing is performed after interpolation processing.

  FIG. 4 is a block diagram of a portion that performs image quality correction processing in the image processing unit 31. As shown in FIG. 4, the image processing unit 31 performs a γ processing unit 51 that performs γ correction processing, a brightness correction unit 52 that performs brightness correction processing, a gradation processing unit 53 that performs gradation processing, and color correction processing. A color correction unit 54, a noise correction unit 55 that performs noise reduction processing, and a sharpness processing unit 56 that performs sharpness processing are provided. In addition, in order to calculate parameters used in each processing unit, a thinning unit 57 that creates a reduced image by thinning out the image S0 before processing, and parameters used when processing in each processing unit is performed from the reduced image. A tone curve for calculating a tone curve used in the parameter calculating unit 58, a face detecting unit 59 for detecting a face from the reduced image, a face brightness calculating unit 60 for calculating the average brightness of the detected face, and a tone processing unit 53 A calculation unit 61 is provided. The brightness correction unit 52 may correct only the brightness of the face.

  The parameter calculation unit 58 calculates a feature value such as an average value, maximum brightness, minimum brightness, and high frequency component of all pixels of the reduced image, and based on the feature value, γ correction, brightness correction, color correction, noise correction, and Calculate parameters for sharpness processing. Specifically, the γ correction amount, the brightness correction amount, the color correction amount, the noise correction amount, and the enhancement degree of sharpness processing are calculated as parameters. Note that any known method can be used as a method for calculating these parameters.

  Further, as will be described later, when an image is not acquired by low-luminance shooting, when acquired by shooting using the flash 24, and even when low-luminance shooting is performed, When the face is not included, the parameter calculation unit 58 calculates a gradation curve as a gradation processing parameter based on the feature amount. On the other hand, when the image is acquired with low brightness shooting without using the flash 24 and a face is detected from the image acquired by shooting, the gradation curve calculation unit 61 calculates the gradation curve as described later. To do.

  The face detection unit 59 detects a rectangular region (face region) surrounding the face from the reduced image by a template matching method, a method using a face discriminator obtained by machine learning learning using a large number of sample images of a face, and the like. Detect as a face. Note that the method for detecting a face is not limited to this. For example, a method for detecting a rectangular region having a skin color in an image and surrounding the contour shape of the face as a face, and a region forming the face contour shape as a face. Any method such as a detection method can be used. When the image includes a plurality of faces, the face detection unit 59 detects all the faces. Only when a face is detected, information indicating the position of the detected face is output to the face luminance calculation unit 60. When no face is detected from the image, the face detection unit 59 outputs information to that effect to the parameter calculation unit 58.

  The face luminance calculation unit 60 calculates the average luminance Yf_ave of the pixels included in the area corresponding to the face area detected from the reduced image, for the image after brightness correction. If a plurality of faces are detected, the average luminance Yf_ave of all face areas is calculated.

  The gradation curve calculation unit 61 calculates an S-shaped gradation curve with the minimum luminance, maximum luminance, and average luminance Yf_ave of the face area that can be taken by the reduced image as fixed points. For example, if the reduced image is an 8-bit image, the S-point with (0, 0), (255, 255) and (Yf_ave, Yf_ave) as fixed points on the input-output plane that defines the characteristics of the gradation curve. The character gradation curve is calculated. Hereinafter, the calculation of the gradation curve will be specifically described.

  FIG. 5 is a diagram for explaining the calculation of the gradation curve. First, the gradation curve calculation unit 61 sets the lowest luminance (0, 0), the highest luminance (255, 255), and the average facial luminance (Yf_ave, Yf_ave) as fixed points. In FIG. 5, it is assumed that the value of the average luminance Yf_ave is 80. Next, the input value Yin_h of the highlight side fixed point for determining the fixed point on the highlight side and the fixed point on the shadow side according to the following formulas (1) and (2) according to the value of the average luminance Yf_ave. And the input value Yin_d of the shadow side fixed point is calculated. According to Expressions (1) and (2), the input value Yin_h is an intermediate value between the average luminance Yf_ave and the maximum luminance 255, and the input value Yin_d is an intermediate value between the average luminance Yf_ave and the minimum luminance 0.

Yin_h = Yf_ave + (255−Yf_ave) / 2 (1)
Yin_d = Yf_ave / 2 (2)
Further, the gradation curve calculation unit 61 determines the highlight-side fixed point and the shadow-side fixed point according to the value of the average luminance Yf_ave, and the highlight-side fixed point output value Yout_h and the shadow-side fixed point. The point output value Yout_d is determined. Specifically, referring to the relationship between the output values Yout_h and Yout_d of the highlight side and the shadow side fixed point according to the predetermined range of the value of the average luminance Yf_ave as shown in FIG. The output values Yout_h and Yout_d of the side and shadow side fixed points are determined. In FIG. 6, 0 to 40 in the section of the average luminance Yf_ave is 0 or more and less than 40. The relationship shown in FIG. 6 is stored in the internal memory 35 as a table.

  Then, the gradation curve calculation unit 61 sets a fixed point (Yin_h, Yout_h) on the highlight side and a fixed point (Yin_d, Yout_d) on the shadow side, and sets the lowest luminance (0, 0) and the highest luminance (255, 255). ) And the average luminance of the face (Yf_ave, Yf_ave), an S-shaped gradation curve passing through five fixed points is calculated. At this time, as a function for calculating the S-shaped gradation curve, a polynomial approximation function may be used as shown in the following equation (3).

y = a (n) × x ^ n + a (n-1) × x ^ n-1 + a (n-2) × x ^ n-2 +… a1 × x (3)
When Yout_h = Yin_h and Yout_d = Yin_d, the gradation curve is a straight line in the section.

  When gradation processing is performed using the gradation curve calculated in this way, particularly when the image is dark and the contrast is poor, the contrast can be increased and the image can be sharpened. Further, since the brightness of the face is not changed by the gradation processing, the contrast of the face is not extremely increased.

  The condition determination unit 62 determines whether or not the image is obtained by low-luminance shooting based on the exposure value calculated by the AE processing unit 29. Further, it is determined whether or not a face is included based on whether or not it is obtained using the flash 24 and the face detection result by the face detection unit 59. When it is determined that the image is acquired by low-luminance shooting, the flash 24 is not used, and a face is further included, the determination result is set as the first determination result, and the determination result is set as the parameter calculation unit 58 and the face luminance. It outputs to the calculation part 60 and the gradation curve calculation part 61. Whether or not low-luminance shooting is performed is determined by determining low-luminance shooting when the exposure value is 5 EV or less, preferably 3 EV or less. On the other hand, in cases other than the first determination result, the determination result is output to the parameter calculation unit 58, the face luminance calculation unit 60, and the gradation curve calculation unit 61 as the second determination result.

  The compression / decompression processing unit 32 generates an image file by compressing the image data of the main image processed by the image processing unit 31 in a compression format such as JPEG. A tag storing incidental information such as shooting date and time is added to the image file based on the Exif format or the like.

  The media control unit 33 accesses a recording medium 34 that is detachably set on a media throttle (not shown), and controls writing and reading of an image file.

  The internal memory 35 stores various constants set in the digital camera 1, the table shown in FIG. 6 described above, a program executed by the CPU 40, and the like.

  The CPU 40 controls each part of the main body of the digital camera 1 in accordance with signals from various processing units such as the operation button 8 and the AF processing unit 28.

  The data bus 41 is connected to various processing units, the frame memory 26, the CPU 40, and the like, and exchanges image data and various instructions.

  Next, processing performed in the present embodiment will be described. Since the present embodiment is characterized in that image quality correction processing is performed on an image acquired by actual shooting, only the processing after the image is acquired by actual shooting will be described in the following description. FIG. 7 is a flowchart showing processing performed in the present embodiment. When an image is acquired by actual shooting, that is, a digital image acquired by shooting is stored in the frame memory 26 and further subjected to interpolation processing, the thinning unit 57 thins out pixels of the image after interpolation processing to reduce the reduced image. Is generated (step ST1). Then, the face detection unit 59 detects a face from the reduced image (step ST2).

  On the other hand, the condition determination unit 62 determines whether the image is acquired by low-luminance shooting, whether the image is acquired using the flash 24, and whether a face is included. Determine (determination process, step ST3).

  When the determination result is the first determination result, the parameter calculation unit 58 calculates parameters for γ correction, brightness correction, color correction, noise correction, and sharpness processing (first parameter calculation, step ST4). Then, the γ processing unit 51 performs γ correction (step ST5), and the brightness correction unit 52 corrects the brightness of the image (step ST6).

  On the other hand, the face luminance calculation unit 60 calculates the average luminance Yf_ave of the face included in the image after brightness correction (step ST7), and the gradation curve calculation unit 61 uses the average luminance Yf_ave as described above. A tone curve is calculated (step ST8).

  Then, the gradation processing unit 53 performs gradation processing using the gradation curve calculated by the gradation curve calculating unit 61 (step ST9). Then, the color correction unit 54 performs color correction processing (step ST10). At this time, the color correction unit 54 may use the color correction parameters determined by the parameter calculation unit 58 as they are, but the image saturation is high by the gradation processing using the gradation curve calculated as described above. For this reason, it is preferable to perform color correction processing by correcting parameters so as to reduce saturation.

  Further, the noise correction unit 55 performs noise correction processing (step ST11). At this time, the noise correction unit 55 may use the noise correction parameter determined by the parameter calculation unit 58 as it is, but the noise of the image is emphasized by the gradation process using the gradation curve calculated as described above. Therefore, it is preferable to perform a noise correction process by correcting parameters so as to reduce more noise. Finally, the sharpness processing unit 56 performs sharpness processing (step ST12), and generates a processed image S1.

  On the other hand, when the determination result is the second determination result, the parameter calculation unit 58 calculates the gradation processing parameters in addition to the parameters of γ correction, brightness correction, color correction, noise correction, and sharpness processing ( Second parameter calculation, step ST13). Then, the γ processing unit 51, the brightness correction unit 52, the gradation processing unit 53, the color correction unit 54, the noise correction unit 55, and the sharpness processing unit 56 perform processing using the parameters calculated by the parameter calculation unit 58, and have been processed. An image S1 is generated (normal image processing, step ST14).

  The processed image S1 is input to the compression / decompression processing unit 32 after YC processing is performed, and the compression / decompression processing unit 32 generates an image file of the processed image S1 (step ST15), and then the media control unit 33 Records the image file on the recording medium 34 (step ST16), and ends the process.

  As described above, in the present embodiment, the average curve Yf_ave of the detected face is used as a fixed point, and a gradation curve that changes the gradation characteristics on the highlight side and the shadow side of the image based on the fixed point is calculated. Since the image quality correction process including the gradation process using the gradation curve is performed on the image, the brightness of the face is not changed by the gradation process. For this reason, the background can have an appropriate contrast according to the gradation curve while maintaining the brightness of the face.

  In particular, since the S-shaped gradation curve is calculated to make the highlight side harder than the average brightness Yf_ave and soften the shadow side from the average brightness Yf_ave, the background is maintained while maintaining the brightness of the face. An appropriate contrast with sharpness corresponding to the gradation curve can be obtained.

  Also, since the tone curve is calculated with the average brightness Yf_ave of the face after γ processing and brightness correction as a fixed point, it is preferable to maintain the γ and face brightness of the corrected image. The background can have an appropriate contrast according to the gradation curve.

  Further, when gradation processing is performed using the S-shaped gradation curve calculated as described above, the contrast of the image increases, but the saturation of the image is enhanced. For this reason, the saturation of the processed image S1 can be made appropriate by performing the color correction processing so as to lower the saturation of the image.

  Further, when gradation processing is performed using the S-shaped gradation curve calculated as described above, although the contrast is increased, noise included in the image is emphasized. For this reason, the processed image S1 in which the noise is reduced can be obtained by performing the noise reduction process so as to reduce the noise.

  In the above embodiment, when it is determined that the image is acquired by low luminance shooting, the flash 24 is not used, and a face is further included, the gradation curve calculation unit 61 calculates the gradation curve. However, without providing such a condition, the gradation curve calculation unit 61 performs gradation only when a face is detected regardless of whether low-luminance photography or photography using the flash 24 is used. A curve may be calculated.

  In the above embodiment, as shown in FIG. 5, an S-shaped gradation curve is calculated that makes the highlight side harder than the average luminance Yf_ave and softens the shadow side more than the average luminance Yf_ave. As shown in FIG. 8, the fixed point is the fixed point with the average luminance Yf_ave of the face as a fixed point, such as an S-shaped gradation curve that softens the highlight side with respect to the average luminance Yf_ave and hardens the shadow side with respect to the average luminance Yf_ave. If the gradation curve changes the gradation characteristics on the highlight side and shadow side of the reference image, the gradation curve may be calculated as desired by the photographer.

  In the above embodiment, the detected face average brightness Yf_ave is a fixed point. However, the brightness of one pixel specified in the detected face or the intermediate brightness of the face area including the detected face, etc. The value of may be a fixed point.

  In the above embodiment, the image processing apparatus according to the present invention is applied to the digital camera 1, but the image processing apparatus may be used alone. In this case, various interfaces for inputting an image acquired by photographing, an exposure value, and the like are used in the image processing apparatus.

  In the above-described embodiment, the condition determination unit 62 determines whether or not low-luminance shooting is performed based on the exposure value. May be determined. In this case, when the ISO sensitivity is 1600 or more, it may be determined that the low-luminance shooting is performed.

  Although the embodiment of the present invention has been described above, a program that causes a computer to function as means corresponding to the above-described image processing unit 31 and perform processing as shown in FIG. 7 is also one of the embodiments of the present invention. It is. A computer-readable recording medium that records such a program is also one embodiment of the present invention.

The figure (front side) which shows the external appearance of the digital camera to which the image processing apparatus by embodiment of this invention is applied The figure (back side) which shows the appearance of the digital camera to which the image processing device by an embodiment of the present invention is applied. 1 is a schematic block diagram showing an internal configuration of a digital camera to which an image processing apparatus according to an embodiment of the present invention is applied. Block diagram of the portion that performs image quality correction processing in the image processing unit Diagram for explaining the calculation of gradation curve The figure which shows the relationship of the output value Yout_h and Yout_d of the highlight side and the shadow side fixed point according to the value of the average luminance Yf_ave A flowchart showing processing performed in the present embodiment Diagram showing another example of gradation curve

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Digital camera 2 Release button 5 Monitor 10 Image pick-up part 31 Image processing part 51 γ processing part 52 Brightness correction part 53 Tone processing part 54 Color correction part 55 Noise correction part 56 Sharpness processing part 57 Decimation part 58 Parameter calculation part 59 Face Detection unit 60 Face luminance calculation unit 61 Gradation curve calculation unit 62 Condition determination unit

Claims (9)

Face detection means for detecting a face from an image acquired by photographing;
A gradation curve calculating means for calculating a gradation curve for changing the gradation characteristics on the highlight side and the shadow side of the image based on the fixed point, the luminance vicinity of the detected face as a fixed point;
An image processing apparatus comprising: an image processing unit configured to generate a processed image by performing an image quality correction process including a gradation process using the gradation curve on the image.   2. The image processing apparatus according to claim 1, wherein the gradation curve calculating means is a means for calculating a gradation curve having an average luminance of a face area including the detected face as a fixed point.   When the image quality correction process includes a brightness correction process, the gradation curve calculation means is a means for calculating a gradation curve with the brightness vicinity of the face after the brightness correction as a fixed point. The image processing apparatus according to claim 1 or 2.   2. The gradation curve calculating means is a means for calculating a gradation curve with the vicinity of the brightness of the face after the γ processing as a fixed point when the image quality correction processing includes γ processing. The image processing apparatus according to claim 1.   When the image is obtained by low-luminance shooting, the gradation curve calculation means hardens the highlight side with respect to the fixed point and softens the shadow side with respect to the fixed point. 5. The image processing apparatus according to claim 1, wherein the image processing apparatus is a means for calculating a curve.   The image processing means is means for performing the color correction processing so as to lower the saturation of the image after the gradation processing when the image quality correction processing includes color correction processing. The image processing apparatus described.   6. The image processing unit according to claim 5, wherein when the image quality correction processing includes noise reduction processing, the image processing means performs the noise reduction processing so as to lower noise of the image after the gradation processing. Or the image processing apparatus of 6. Detect faces from images acquired by shooting,
A gradation curve that changes the gradation characteristics on the highlight side and the shadow side of the image with the fixed vicinity of the detected luminance of the face as a fixed point,
An image processing method, wherein a processed image is generated by performing image quality correction processing including gradation processing using the gradation curve on the image. A procedure for detecting a face from an image acquired by shooting;
A procedure for calculating a gradation curve that changes the gradation characteristics on the highlight side and the shadow side of the image with reference to the fixed point in the vicinity of the detected luminance of the face as a fixed point;
A program for causing a computer to execute an image processing method, comprising: generating a processed image by performing image quality correction processing including gradation processing using the gradation curve on the image. .

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