JP2010010976A - Photographic image processing method, photographic image processing program, and photographic image processing device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processing method, an image processing program and an image processing device, which can effectively process photographic image data, photographed by a digital camera, to effectively suppress grainy noise and color noise respectively in a state wherein a contour is never out of focus. <P>SOLUTION: The photographic image processing method for suppressing grainy noise included in the photographic image data photographed by the digital camera includes: a luminance component image extraction step of extracting luminance component image data from the photographic image data; a luminance filter processing step of performing filter processing on the luminance component image data with a running average filter with a first filter size to generate luminance smoothed image data; and a luminance substitution processing step of dividing the luminance component image into pixel blocks of predetermined size and substituting luminance components, showing maximum and minimum values, extracted from the respective divided areas for luminance components of corresponding pixels of the luminance smoothed image data. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a photographic image processing method, a photographic image processing program, and a photographic image processing apparatus that suppress granular noise included in photographic image data.

  When an image taken with a digital camera is observed, it is observed that fine granular noise is superimposed on the image. In particular, noise that is rough in the dark part of the image is conspicuous, and similar noise appears in the entire image in an image shot in a dark place without flash emission.

  These noises are caused by the characteristics of the elements such as the reset noise and dark current noise of the image sensor.The imaging environment is worse, that is, the lower the illuminance of the subject, the better the noise component. Noise is enhanced when the brightness is corrected.

  By the way, as a technique for suppressing granular unevenness based on the size of a pigment cloud contained in a film image photographed by an optical camera, photographic image data converted into a digital image via a film scanner is converted into a predetermined image based on the resolution. There is a process of performing filter processing using a median filter or a Gaussian filter of a filter size, that is, processing for replacing a certain pixel with a predetermined average value obtained from surrounding pixels, but it is possible to sharpen the outline portion of the image. If such a blurring process is performed after the sharpening process to give a sharpness, the outline is blurred, so the meaning of the sharpening is lost. When the sharpening process is performed after the blurring process described above, the fine structure ( There is an inconvenience that details are lost.

  Therefore, photographic image data is divided into blocks by a predetermined number of pixels, the average value and variance value of each area are obtained, and a flat image area with a small variance value is subjected to strong smoothing processing, and an image including an outline with a large variance value Although it is conceivable to perform weak smoothing processing on the area, according to this method, if an image area including a contour is present in the block, the weak smoothing processing is uniformly executed. The noise suppression effect is reduced in the band-like region of the width, and a preferable result is not obtained.

  In Patent Document 1, as an image processing method for performing weighted average filter processing on photographic image data converted into a digital image via a film scanner, a step of sequentially setting a pixel of interest for each RGB pixel component constituting the photographic image data Calculating a difference value of pixel values between each peripheral pixel located in the calculation region for the weighted average filtering process centered on the target pixel and the target pixel, and weighted average filtering according to the difference value There has been proposed a method including a step of determining a weighting factor used for processing, and a step of executing a weighted average filtering process using the weighting factor to obtain a corrected pixel value of a target pixel.

According to this method, there is a predetermined relationship between the pixel value of the pixel of interest and its surrounding pixels when the pixel of interest is located in the flat region and when it is located in the contour region. By setting a weighting factor that gives a strong influence, granular noise can be suppressed not only in flat areas but also in the contour and its vicinity, and granular noise suppression that maintains the fine details and texture of photographs can be realized. It becomes.
JP 2006-302023 A

  However, since photographic image data taken with a digital camera is usually orthogonally transformed after the color difference data is reduced to 1/2 or 1/4 when compressed into a JPEG image, it is compared with luminance data. In combination with the reduction in the data amount of the color difference data, the color noise tends to appear larger than the luminance noise. In the method of performing weighted average filtering for each color component described in Patent Document 1 described above, the luminance noise There was a problem that color noise could not be removed properly.

  In addition, since processing is performed with a weighted average filter having a size (3 × 3 pixels) smaller than the block size (usually 8 × 8 pixels) when compressed into a JPEG image, there is a problem in that noise removal accuracy is not improved. .

  In view of the above-described conventional drawbacks, the present invention provides a photographic image processing method and photographic image processing capable of effectively suppressing granular luminance noise and color noise in a state in which no outline is blurred with respect to photographic image data. The object is to provide a program and a photographic image processing apparatus.

  In order to achieve the above-mentioned object, the first characteristic configuration of the photographic image processing method according to the present invention is to suppress the granular noise included in the photographic image data as described in claim 1 of the claims. Luminance component image extraction step for extracting luminance component image data from the photographic image data, and luminance smoothing by filtering the luminance component image with a weighted average filter of a first filter size A luminance filter processing step for generating image data; and the luminance component image is divided into pixel blocks of a predetermined size, and luminance components indicating the maximum value and the minimum value extracted from each divided region are converted into the luminance smoothed image data; And a luminance replacement processing step for replacing the luminance component of the corresponding pixel.

  In the luminance filter processing step, the luminance component image on which fine luminance noise of approximately one pixel unit is superimposed is filtered by the weighted average filter of the first filter size, and the luminance smoothed image data appropriately suppressed in noise is obtained. Generated. Then, in the luminance replacement processing step, the luminance component image of the original image is divided into pixel blocks of a predetermined size, and pixels indicating the maximum value and the minimum value are extracted from each divided region and processed in the luminance filter processing step. By replacing the luminance component of the corresponding pixel in the luminance component image, a large value of luminance noise is reduced.

  In the luminance component image after being processed in the luminance filter processing step, luminance noise is sufficiently suppressed in the contour region, but tends to be a smooth image in the flat region, and the fine structure in the image (detail) May disappear. However, by replacing part of the pixel data of such an image with the pixel data of the noise area of the original image, large luminance noise can be suppressed from the luminance component image of the original image, and the remaining small luminance value A moderate roughness is maintained by noise.

  According to the second feature configuration, as described in claim 2, in addition to the first feature configuration described above, the luminance replacement processing step may be performed when the luminance component replacement processing for all pixel blocks is completed. The process of executing the luminance component replacement process again for a new pixel block obtained by dividing the center pixel of the block vertically, horizontally, or diagonally by a predetermined pixel is repeated a predetermined number of times.

  If the number of executions of the luminance replacement processing step is one, two pixels indicating the maximum value and the minimum value included in each pixel block are replaced with the pixels of the luminance component image after being processed in the luminance filter processing step. However, luminance noise is not always sufficiently suppressed.

  However, if the same processing is executed a plurality of times for the same pixel block, the image becomes a reverse image. Therefore, by repeating the process of replacing the luminance component again for a new pixel block divided so that the center pixel of the pixel block shifts by a predetermined pixel vertically, horizontally, or diagonally, it can be performed smoothly. Thus, it is possible to effectively suppress luminance noise while avoiding the image.

  In the third feature configuration, in addition to the first or second feature configuration described above, the luminance filter processing step includes a maximum value and a minimum value extracted in the luminance replacement processing step. This is performed on the luminance component pixel indicating the value, thereby reducing the number of computations and enabling high-speed processing.

  In the fourth feature configuration, in addition to any one of the first to third feature configurations described above, the luminance component image extraction step includes each of the photographic image data as described in claim 4. An RGB-YCbCr conversion processing step for converting the RGB color component of the pixel into a luminance color-difference component of YCbCr, and each of the color-difference component images obtained in the RGB-YCbCr conversion processing step is larger than the first filter size. A color difference filter processing step for generating color difference smoothed image data by filtering with a weighted average filter having a second filter size, the luminance component obtained in the luminance replacement processing step, and the color difference filter processing step. A YCbCr-RGB conversion processing step for inversely converting the luminance color difference component composed of the color difference components into an RGB color component; Located in.

  For example, in a photographic image taken with a digital camera, compared to a luminance component image in which fine luminance noise of about one pixel unit is superimposed, the influence of the JPEG conversion processing, the Bayer arrangement of the color filter provided in the image sensor, etc. Therefore, the color difference component image is notably suppressed in the color difference filter processing step using the weighted average filter of the second filter size larger than the first filter size because a wide range of color noise over a plurality of pixels is remarkable. Color difference image data is obtained.

  In the YCbCr-RGB conversion processing step, the luminance color difference component composed of the luminance component obtained in the luminance substitution processing step and the color difference component filtered in the color difference filtering processing step is inversely converted into an RGB color component, and the color A photographic image in which both noise and luminance noise are satisfactorily suppressed can be obtained.

  In the fifth feature configuration, as described in claim 5, in addition to the fourth feature configuration described above, a filter size larger than the block size for compression by JPEG is selected as the second filter size. There is in point.

  By setting the second filter size larger than the block size when compressed into a JPEG image, it is possible to effectively suppress color noise that tends to appear at a size larger than the luminance noise.

  In the sixth feature configuration, as described in claim 6, in addition to any of the first to fifth feature configurations described above, the weighted average filter includes a center pixel and a peripheral pixel within a filter size. It is determined dynamically according to the target image data so that the difference becomes zero or a large filter coefficient in the vicinity of a predetermined threshold value for determining whether the image is an edge portion of the image, and a small filter coefficient that deviates from the threshold value. It is in the point that it is a filter.

  The inventor of the present application has found that it is possible to find out whether the region is close to the contour or away from the region based on the difference between the pixel values of the pixel of interest and the surrounding pixels. In other words, the difference between the center pixel and the surrounding pixels within the filter size is set to a large filter coefficient in the vicinity of a predetermined threshold value for determining whether it is zero or the contour of the image, and the filter coefficient becomes small enough to deviate from the threshold value. By setting to, the granular noise can be sufficiently suppressed not only in the flat region but also in the contour and its vicinity.

The characteristic configuration of the photographic image processing program according to the present invention is the photographic image processing program for suppressing granular noise included in the photographic image data, as described in claim 7, wherein each pixel constituting the photographic image data RGB-YCbCr conversion processing step for converting the RGB color components into YCbCr luminance color-difference components, and the luminance component image obtained in the RGB-YCbCr conversion processing step is filtered with a weighted average filter of the first filter size A luminance filter processing step for generating luminance smoothed image data, and dividing the luminance component image into pixel blocks of a predetermined size, and extracting the luminance component indicating the maximum value and the minimum value extracted from each divided region as the luminance A luminance replacement processing step for replacing the luminance component of the corresponding pixel of the smoothed image data, and the RGB-YCbC Each of the color difference component images obtained in the conversion processing step is filtered with a weighted average filter having a second filter size larger than the first filter size to generate color difference smoothed image data; and A YCbCr-RGB conversion processing step for inversely converting a luminance color difference component composed of the luminance component obtained in the luminance substitution processing step and the color difference component filtered in the color difference filtering processing step into an RGB color component;
Is to make the computer execute.

  The photographic image processing apparatus according to the present invention is characterized in that, as described in claim 8, the photographic image processing apparatus is a photographic image processing apparatus that suppresses granular noise included in photographic image data, each pixel constituting the photographic image data. RGB-YCbCr conversion processing unit for converting RGB color components into YCbCr luminance color-difference components, and luminance component images obtained by the RGB-YCbCr conversion processing unit using a weighted average filter of the first filter size A luminance filter processing unit that generates luminance smoothed image data, and the luminance component image is divided into pixel blocks of a predetermined size, and luminance components indicating maximum and minimum values extracted from each divided region are A luminance replacement processing unit that replaces the luminance component of the corresponding pixel of the smoothed image data, and a color difference component image obtained by the RGB-YCbCr conversion processing unit; A color difference filter processing unit that generates color difference smoothed image data by filtering with a weighted average filter having a second filter size larger than the first filter size, and a luminance component obtained by the luminance replacement processing unit, And a YCbCr-RGB conversion processing unit that reversely converts a luminance color difference component composed of the color difference components filtered by the color difference filter processing unit into RGB color components.

  As described above, according to the present invention, a photographic image processing method and photographic image processing capable of effectively suppressing each of granular luminance noise and color noise without blurring the outline of photographic image data. A program and a photographic image processing apparatus can be provided.

  Embodiments of a photographic image processing apparatus according to the present invention will be described below.

  As shown in FIG. 1, a photographic image processing apparatus 1 performs an exposure process based on output image data on a photographic paper P, develops the exposed photographic paper, and generates and outputs a photographic print. And an operation station 3 for setting and inputting print order information for the photographic image, performing various image correction processes, and outputting output image data edited from the original image to the photographic printer 2.

  The operation station 3 includes a film scanner 31 that reads an image from a developed photographic film F, and a media driver that reads image data from an image data storage medium M such as a memory card in which image data shot by a digital still camera or the like is stored. 32, a general-purpose computer as the controller 33, and the like.

  As shown in FIGS. 1 and 2, the photographic printer 2 has two systems of photographic paper magazines 21 containing roll-shaped photographic paper P, and the photographic paper P drawn from the photographic paper magazine 21 in a predetermined print size. A sheet cutter 22 for cutting, a back print unit 23 for printing print information such as a frame number on the back of the cut photographic paper P, an exposure unit 24 for exposing the photographic paper P based on the print data, and a post-exposure unit A development processing unit 25 including a plurality of processing tanks 25a, 25b, and 25c filled with processing solutions for developing, bleaching, and fixing the photographic paper P is disposed along the conveyance path of the photographic paper P, and development processing is performed. A lateral feed conveyor 26 that discharges the photographic paper P that has been dried later, and a sorter 27 that sorts a plurality of photographic papers (photo prints) P stacked on the lateral feed conveyor 26 in order units. To have.

  The exposure unit 24 outputs a three-color laser beam bundle of RGB that is modulated based on the print data in the main scanning direction orthogonal to the conveyance direction with respect to the photographic paper P conveyed in the sub-scanning direction by the conveyance mechanism 28. Then, an exposure head 24a for exposure is accommodated.

  A transport mechanism 28 composed of a plurality of roller pairs that transport the printing paper P at a predetermined process speed is disposed in the exposure unit 24 and the development processing unit 25 disposed along the transport path. A chucker-type transport mechanism 28a capable of transporting the paper P in multiple rows is provided.

  A controller 33 provided in the operation station 3 operates under the management of a general-purpose operating system, and is installed with a plurality of application programs for executing various image processing and input / output control of the photo processing apparatus 1. As an operation interface, a monitor 34, a keyboard 35, a mouse 36, and the like are connected. The application program includes an image processing program according to the present invention.

  The controller 33 is a block in which the hardware and software cooperate to execute a photo processing process, and will be described below in each functional block.

  As shown in FIG. 3, the controller 33 receives photographic image data as an original image read by the film scanner 31 or the media driver 32, performs a predetermined preprocessing, and transfers it to the memory 41. A print operation information and image editing information is displayed on the screen of the monitor 34, and a graphic operation screen for displaying operation icons for inputting necessary data is generated for the print operation information or a keyboard for the displayed graphic operation screen. 35, a graphic user interface unit 42 that generates various control commands based on input operations from the mouse 36, photographic image data transferred from the image input unit 40, photographic image data after correction processing by the image processing unit 47, Correction parameters at that time, and also set A memory 41 in which lint order information is partitioned and stored in a predetermined area, an order processing unit 43 that generates print order information, and each frame image or a predetermined number of frames for each photographic image data stored in the memory 41 An image processing unit 47 that performs density correction processing, contrast correction processing, and the like on the image is provided.

  Further, a display control unit 46 including a video RAM for displaying the image data developed in the memory 41 based on a display command from the graphic user interface unit 42 and various input / output graphic data on the monitor 34, and the like; A print data generation unit 44 that generates print data for outputting the final corrected image for which various correction processes have been completed to the photographic printer 2, and a storage medium such as a CD-R for the final corrected image according to the customer's order A formatter unit 45 for converting to a file format for writing to the file.

  The film scanner 31 is configured to operate in two modes: a pre-scan mode for reading an image recorded on the film F at a high speed although it is a low resolution and a main scan mode for reading at a high resolution although it is a low resolution. Various correction processes are performed on the low-resolution image read in the mode, and the final correction for the high-resolution image read in the main scan mode based on the correction parameters stored in the memory 41 at that time. The process is executed and output to the printer 2.

  Similarly, the image file read from the media driver 32 includes a high-resolution captured image and its thumbnail image, and various correction processes described later are performed on the thumbnail image and stored in the memory 41 at that time. Based on the correction parameters, the final correction processing for the high-resolution captured image is executed. When the thumbnail image is not included in the image file, the thumbnail image is generated from the high-resolution captured image by the image input unit 40 and transferred to the memory 41.

  As described above, various editing processes that are frequently trial and error are performed on low-resolution images, so that the calculation load of the controller 33 is reduced.

  The image processing unit 47 includes a distortion correction unit 50 that corrects distortion caused by the photographic lens with respect to photographic image data that is an original image stored in the memory 41, and a granular noise suppression processing unit 51 that suppresses granular noise. A sharpening processing unit 52 that enhances an edge of an image and suppresses noise, a color correction unit 53 that adjusts a color balance so as to reproduce a natural color, and an image size suitable for the size of a photographic print A plurality of image processing blocks such as the enlargement / reduction processing unit 54 are provided.

  The granular noise suppression processing unit 51 functions as a granular noise suppression processing unit 51 for film images that suppresses granular noise included in image data read from the photographic film F in the main scan mode, and an image processing apparatus according to the present invention. In addition, a granular noise suppression processing unit 51 for a digital camera photographed image that suppresses granular noise included in high-resolution image data read from the media driver 32 is provided.

  Hereinafter, processing of photographic image data taken by a digital camera input from the media driver 32 will be described in detail. However, photographic image data read from the photographic film F in the main scan mode can be processed in the same manner. is there.

  When a plurality of thumbnail image data and high resolution image data read from the media driver 32 are stored in the memory 41, several frames of photographic images based on the thumbnail image data and a graphic operation screen are displayed on the screen of the monitor 34. . Normally, since the digital image stored in the medium is compressed by the JPEG method, image data obtained by inverse conversion and decompression is stored.

  For each frame image displayed on the screen of the monitor 34, the order processing unit 43 sets the print conditions, that is, the number of prints, the print size, and the like through the operator's operation on the graphic operation screen.

  Further, distortion correction, sharpening processing, and color correction are executed for each frame image by the image processing unit 47 through an operator's operation, and the image correction processing conditions set at this time are stored in the memory 41. .

  When the print condition setting and correction processing operations for each frame image displayed on the screen of the monitor 34 are completed, the screen is scrolled to the next screen, and the same processing is executed for all the frame images.

  When all the operation processes are completed and a print output operation is performed via the graphic operation screen, distortion correction, granular noise suppression process, and sharpening process are performed on the high-resolution photographic image data stored in the memory 41. Image processing such as color correction processing and enlargement / reduction processing is executed in order, and the image data after the image processing is converted and generated into print data by the print data generation unit 44 and output to the photographic printer 2.

  Distortion correction, sharpening processing, and color correction processing for high-resolution photographic image data are automatically corrected based on correction processing conditions set for thumbnail images, that is, correction processing conditions stored in the memory 41. Processing is executed.

  The granular noise suppression processing unit 51 for a digital camera photographed image according to the present invention will be described in detail below.

  As shown in FIG. 4, the granular noise suppression processing unit 51 includes an RGB-YCbCr conversion processing unit 510 that converts RGB color components of each pixel constituting photographic image data into YCbCr luminance color difference components, and RGB-YCbCr conversion. A luminance filter processing unit 512 that generates luminance smoothed image data by filtering the luminance component image obtained by the processing unit 510 with a weighted average filter having a first filter size; A luminance replacement processing unit 514 that divides the blocks into luminance components indicating the maximum value and the minimum value extracted from each divided region with the luminance components of the corresponding pixels of the luminance smoothed image data; and an RGB-YCbCr conversion processing unit Each of the color difference component images obtained in 510 is filled with a weighted average filter having a second filter size larger than the first filter size. The color difference filter processing unit 516 (516a, 516b) that generates color difference smoothed image data by processing, the luminance component obtained by the luminance replacement processing unit 514, and the color difference component filtered by the color difference filter processing unit 516 The YCbCr-RGB conversion processing unit 518 is provided to reversely convert the luminance / chrominance component to be converted into RGB color components.

The RGB-YCbCr conversion processing unit 510 is based on the following conversion formula, and is photographic image data that is a high-resolution original image read from the memory 41 (for example, about 8264 pixels, about 3264 pixels wide × 2448 pixels high) The color components of R (red), G (green), and B (blue) (hereinafter referred to as “RGB”) of each pixel constituting each pixel are converted into luminance color difference components and stored in the memory 41. Store.
Y = 0.29900R + 0.58700G + 0.11400B
Cb = −0.16874R−0.33126G + 0.50000B
Cr = 0.50000R-0.41869G-0.0811B

  In the luminance filter processing unit 512, the luminance component image is subjected to filter processing by a weighted average filter having a first filter size of about 7 × 7, and luminance smoothed image data is generated.

  The color difference filter processing unit 516 (516a, 516b) has a second filter size of about 9 × 9 or 11 × 11 larger than the first filter size (7 × 7) for each of the color difference component images. Filter processing is executed by the weighted average filter, and color difference smoothed image data is generated.

  Normally, in the JPEG method, YCRCb-converted pixels are subjected to DCT conversion for each 8 × 8 block, the obtained frequency components are quantized, and quantized data arranged by zigzag scanning is Huffman encoded. The color difference data is thinned out to 1/4 of the luminance data before DCT conversion. This is to reduce the color difference data based on the characteristic that the human eye is sensitive to a small difference in luminance while being relatively unaware of the small difference in hue.

  Therefore, when granular noise, which is the cause of roughness appearing in a photographic image taken with a digital camera, is divided into luminance noise and color noise, luminance noise appears in units of approximately one pixel, whereas color noise is relatively large. There is a characteristic that it appears as a pixel size and the tendency has a correlation with the block size at the time of DCT conversion.

  Therefore, in order to suppress color noise, it is preferable to set the second filter size to a filter size larger than the block size for compression by JPEG. In this embodiment, about 9 × 9 or 11 × 11. The filter size is set. On the other hand, in order to suppress luminance noise generated in a small pixel, it is preferable to set a filter size smaller than the second filter size.

  As a weighted average filter, a general Gaussian filter or a bilateral filter excellent in the preservation characteristics of the contour of the subject can be adopted, but in this embodiment, the region close to the contour without blurring the contour of the subject. A dynamic filter that can appropriately suppress granular noise is used.

  The target image is such that the difference between the center pixel and the surrounding pixels within the filter size is zero or a large filter coefficient in the vicinity of a predetermined threshold value for determining whether the image is an edge portion of the image, and the filter coefficient is small enough to deviate from the threshold value. It is a weighted average filter that is dynamically determined according to data.

As shown in FIGS. 5A and 5B, the filter coefficient F _{i, j} of the weighted average filter is 0 to 1 depending on the difference in pixel value between the central pixel P _0,0 and the peripheral pixel P _{i, j.} Is determined based on a coefficient determination function (F _{i, j} = f (Δ)) that outputs a value in the range of. Actually, each filter coefficient is determined by referring to table data in which filter coefficients corresponding to the difference Δ are previously defined according to the coefficient determination function.

As shown in FIG. 6, the coefficient determination function is an area close to or away from the contour of the subject based on the difference Δ between the pixel values of the _target pixel P _0,0 and its surrounding pixels P _{i, j.} When the difference Δ is 0, that is, when the luminance value or the color difference value of the central pixel and the peripheral pixel are equal, the filter coefficient F _{i, j} is set to 1 and the luminance value of the central pixel and the peripheral pixel or threshold and filter coefficient F _i when equal color difference value set in _{advance, j} is set to 1, the more the filter coefficient luminance values or chrominance value of the center pixel and peripheral pixels is reduced from the threshold F _{i, j} is the small value This is a function that is set and is defined as a Gaussian function in which the filter coefficient gradually decreases from 1 within a predetermined width centered on the threshold value.

  The threshold value is a value indicating the boundary of recognizing the difference as “noise” or “part of the subject” when there is a luminance or hue difference between adjacent pixels in the original image data. When the difference is sufficiently larger than the threshold value, the value obtained using a statistical method such as a sensitivity test on the image, the probability that the pixel represents the contour of the subject is high, and when the difference is smaller than the threshold value, the granularity This is an index for determining that the probability of noise is high.

  As the threshold, when the luminance or color difference of each pixel is expressed as an 8-bit numerical value from 0 to 255, it is preferable to adopt a value between 10 and 20, particularly about 16. When the difference Δ is a minute value of 1 or 2, it is recognized as noise, but since it is not so large, by leaving it as it is, an appropriate roughness is maintained and a flat portion becomes a flat part. Such inconvenience can be avoided.

  The luminance filter processing unit 512 and the chrominance filter processing unit 516 sequentially weight each pixel arranged in the row direction from the leftmost pixel of the first row of the processing target image data as a target pixel by the weighted average filter of each filter size. When the average filter processing is repeated and the processing is completed up to the rightmost pixel, the same processing is performed in the row direction from the leftmost pixel in the second row, and the processing is repeated up to the rightmost pixel in the last row.

  By performing such processing, granular noise can be appropriately suppressed up to the vicinity of the contour region of the subject.

  It should be noted that since there is no actual pixel in the end region of the processing target image data, a dummy pixel having the same pixel value as that of the end pixel is generated and processed. However, the effective image size actually printed is the original image. Since the size is slightly smaller than the size, it does not affect the print image.

As shown in FIG. 7A, the luminance replacement processing unit 514 divides the luminance component image data IY extracted by the RGB-YCbCr conversion processing unit 510 into pixel blocks of 7 × 7 pixel size, and each divided region is divided. The luminance components Y _max and Y _min indicating the maximum value and the minimum value extracted from R _{i, j} are replaced with the luminance components of the corresponding pixels of the luminance smoothed image data IY ′ smoothed by the luminance filter processing unit 512. .

  When the luminance replacement processing unit 514 completes the luminance component replacement processing for all the pixel blocks, the luminance component processing is performed on a new pixel block obtained by dividing the center pixel of the pixel block by a predetermined pixel vertically, horizontally, or diagonally. The process of executing the replacement process again is repeated a predetermined number of times.

  Specifically, in FIG. 7B, a process of executing a luminance component replacement process for a new pixel block obtained by dividing the center pixel of a pixel block having a size of 7 × 7 pixels by shifting it diagonally downward to the right by one. Is repeated 7 times. Thus, in the case of a 7 × 7 pixel size, it is appropriate to repeat about 7 times.

  Further, for example, as shown in FIG. 7 (c), luminance component replacement is performed on a new pixel block obtained by dividing the center pixel of the pixel block by reciprocating a diagonal line that descends diagonally downward to the right. The process for executing the process can be repeated 14 times.

  Since the size of the above-described image block is merely an example, it may be a 5 × 5 pixel size, and may be changed according to the first filter size used at the time of generating the luminance smoothed image data. In this case, it is appropriate to repeat the process of executing the luminance component replacement process about five times.

  If the number of executions of the luminance replacement processing step is one, two pixels indicating the maximum value and the minimum value included in each pixel block are replaced with the pixels of the luminance component image after being processed in the luminance filter processing step. However, luminance noise is not always sufficiently suppressed.

  However, as described above, when the same processing is executed a plurality of times for the same pixel block, a converse image is formed. Therefore, the luminance component replacement processing is executed again for a new pixel block that is divided so that the center pixel of the pixel block is shifted by a predetermined pixel vertically, horizontally, or diagonally according to the amount of luminance noise of the luminance component image. By repeating the process a predetermined number of times, it is possible to effectively suppress luminance noise while avoiding a crisp image.

In the YCbCr-RGB conversion processing unit 518, a corrected new component composed of the luminance component obtained by suppressing the luminance noise obtained by the luminance substitution processing unit 514 and the color difference component obtained by suppressing the color noise by the color difference filter processing unit 516 is obtained. The luminance color difference component is inversely converted into an RGB color component based on the following equation and output to the sharpening processing unit 52.
R = Y−0.000007Cb + 1.401998Cr
G = Y−0.344133Cb−0.714138Cr
B = Y + 1.772003Cb + 0.000015Cr

  Below, the procedure of each process by the granular noise suppression process part 51 mentioned above is demonstrated based on the flowchart shown in FIG.

  First, when the RGB color component data of each pixel constituting the photographic image data is input to the RGB-YCbCr conversion processing unit 510, the RGB-YCbCr conversion processing step is executed, and the luminance component image data and the color difference component image data are obtained. Is output (S1).

  When the output luminance component image data is input to the luminance filter processing unit 512, a luminance filter processing step (S2) is executed.

  The luminance filter processing step (S2) includes a pixel difference calculation processing step (S21), a weighted average filter coefficient determination processing step (S22), and a weighted average filter processing step (S23).

First, a pixel difference calculation processing step (S21) is executed, and as shown in FIG. 5A, the center pixel P _0,0 and the surroundings of the input luminance component image data according to a predetermined weighted average filter size A difference Δ between the pixel values of the pixels P _{i, j} is calculated.

Subsequently, a weighted average filter coefficient determination processing step (S22) is executed, and as shown in FIGS. 5B and 6, table data in which filter coefficients corresponding to the difference Δ are defined in advance according to a predetermined coefficient determination function. , Each filter coefficient F _{i, j} is determined.

  Subsequently, the weighted average filter processing step (S23) is executed, the filter processing using the weighted average filter determined in the weighted average filter coefficient determination processing step (S22) is executed, and the luminance smoothed image data that is the execution result Then, the luminance component image data before execution is output to the luminance replacement processing unit 514.

  Subsequently, when the luminance smoothed image data is input to the luminance replacement processing unit 514, a luminance replacement processing step (S3) is executed.

  The luminance replacement processing step (S3) includes a pixel block division processing step (S31), a pixel data replacement processing step (S32), an all pixel block end determination processing step (S33), and a predetermined number of times end determination processing step (S34). Consists of.

  First, a pixel block division processing step (S31) is executed, and the input luminance component image data is divided into a plurality of pixel blocks according to how to shift the center pixel position of a predetermined pixel block. Note that at the first execution of this processing step, the central pixel position of the pixel block is executed without shifting.

Subsequently, a pixel data replacement processing step (S32) is executed, and luminance components Y _max and Y indicating the maximum value and the minimum value extracted from each divided region R _{i, j} divided in the pixel block division processing step (S31). _min is replaced with the luminance component of the corresponding pixel of the luminance smoothed image data.

  Subsequently, an all pixel block end determination processing step (S33) is executed, and whether or not the pixel data replacement processing step (S32) has been executed for all the pixel blocks divided in the pixel block division processing step (S31). The pixel data replacement processing step (S32) is repeatedly executed until it is determined and there are no unprocessed divided areas.

  When the pixel data replacement processing step (S32) is executed for all the pixel blocks, it is determined whether the luminance replacement processing step (S3) has been executed a predetermined number of times.

  If the predetermined number of times has not been executed, the pixel block division processing step (S31) is executed again, the center pixel position of the pixel block is shifted according to a predetermined shifting method, and the luminance component image data is newly added to a plurality of pixels. Divided into blocks.

  Subsequently, the pixel data replacement processing step (S32) and the all pixel block end determination processing step (S33) are executed for the new pixel block described above, and the end determination processing step (S34) is executed a predetermined number of times. .

  When the predetermined number of times have been executed, luminance component image data that is the result of repeatedly executing the luminance replacement processing step (S3) a predetermined number of times is output, and the luminance replacement processing step (S3) ends.

  Further, when the color difference component image data output in the RGB-YCbCr conversion processing step (S1) of the RGB-YCbCr conversion processing unit 510 is input to the color difference filter processing unit 516, the color difference filter processing is executed and the filter processing is performed. Luminance color difference component image data composed of color difference components is output (S4).

  Subsequently, the luminance component image data obtained in the luminance substitution processing step (S3) of the luminance substitution processing unit 514 and the luminance / chrominance component image data obtained in the color difference filtering processing step (S4) of the color difference filtering processing unit 516 are represented by YCbCr. When input to the RGB conversion processing unit 518, YCbCr-RGB conversion processing is executed, and RGB color component data is output (S5).

  Each processing by the granular noise suppression processing unit 51 described above is realized by executing a photographic image processing program of the present invention installed in a hard disk provided in the controller 33.

  That is, an RGB-YCbCr conversion processing step for converting a RGB color component of each pixel constituting photographic image data into a luminance color difference component of YCbCr, which is a photographic image processing program for suppressing granular noise included in photographic image data (S1) and a luminance filter processing step of generating luminance smoothed image data by filtering the luminance component image obtained in the RGB-YCbCr conversion processing step (S1) with a weighted average filter of the first filter size ( S2), the luminance component image is divided into pixel blocks of a predetermined size, and the luminance component indicating the maximum value and the minimum value extracted from each divided region is replaced with the luminance component of the corresponding pixel of the luminance smoothed image data. The color difference component images obtained in the luminance replacement processing step (S3) and the RGB-YCbCr conversion processing step are respectively A color difference filter processing step (S4) for generating color difference smoothed image data by filtering with a weighted average filter having a second filter size larger than the filter size, and the luminance component obtained in the luminance substitution processing step (S3); A photographic image processing program for causing a computer to execute a YCbCr-RGB conversion processing step (S5) for inversely converting a luminance color difference component composed of the color difference components filtered in the color difference filter processing step (S4) into an RGB color component. It is installed via a storage medium such as a stored CD or DVD.

  Further, in the luminance replacement processing step (S3), when the luminance component replacement processing for all the pixel blocks is completed, a new pixel block obtained by dividing the center pixel of the pixel block by a predetermined pixel shift vertically, horizontally, or diagonally is used. Thus, a program for repeating the process of replacing the luminance component again a predetermined number of times is included.

  FIG. 10 shows a photographic image obtained as a result of executing the granular noise suppression process on the original image shown in FIG. As can be seen from the photographic image, it can be seen that by performing the granular noise suppression processing, noise such as shadows scattered in flat areas such as clothes and skin around the collarbone is suppressed. It can also be seen that the clothes and background colors are bright and clear.

  Further, when attention is paid to the necklace, it can be seen that the outline of the chain becomes clear and the color of the chain is displayed brightly and clearly. In addition, the shadow-like noise seen on the uneven skin of the neckline near the necklace is suppressed, and a small amount of luminance noise remains, so that the skin texture is displayed without being impaired. Recognize.

  Note that the above-described embodiment is merely an example of the present invention, and it is needless to say that the specific configuration and the like of each block can be changed and designed as appropriate within the scope of the effects of the present invention.

External view of photographic image processing device Illustration of photo printer Functional block diagram of photographic image processing device Functional block diagram of the granular noise suppression processing unit It is explanatory drawing of a weighted average filter, (a) is explanatory drawing which shows the relationship between center pixel _P0,0 and peripheral pixel _{Pi, j} , (b) is explanatory drawing which shows a filter coefficient. Explanatory diagram of coefficient determination function for weighted average filter It is explanatory drawing of a brightness | luminance replacement process step, (a) is explanatory drawing which shows the replacement process of the luminance component pixel of the maximum value and minimum value in a division area, (b) is explanatory drawing which shows how to shift a division area, c) is an explanatory diagram of an example of how to shift divided areas Flowchart for explaining the processing procedure of the granular noise suppression processing unit Original photo image before grain noise suppression processing Photo image after grain noise suppression processing

Explanation of symbols

1: Photo image processing device 51: Granular noise suppression processing unit 510: RGB-YCbCr conversion processing unit 512: Luminance filter processing unit 514: Luminance replacement processing unit 516: Color difference filter processing unit 518: YCbCr-RGB conversion processing unit S1: RGB -YCbCr conversion processing step S2: luminance filter processing step S3: luminance replacement processing step S4: chrominance filter processing step S5: YCbCr-RGB conversion processing step P _{i, j} : peripheral pixels R _{i, j} : divided regions F _{i, j} : Filter coefficient IY: Luminance component image data IY ′: Luminance smoothed image data Y _max : Luminance component pixel Y _min indicating the maximum value in the divided area of the luminance component image data: Minimum in the divided area of the luminance component image data Luminance component pixel indicating value

Claims (8)

A photographic image processing method for suppressing granular noise included in photographic image data,
A luminance component image extraction step for extracting luminance component image data from the photographic image data;
A luminance filter processing step for generating luminance smoothed image data by filtering the luminance component image with a weighted average filter of a first filter size;
Luminance replacement that divides the luminance component image into pixel blocks of a predetermined size and replaces the luminance component indicating the maximum value and the minimum value extracted from each divided region with the luminance component of the corresponding pixel of the luminance smoothed image data Processing steps;
A photographic image processing method.   In the luminance replacement processing step, when the luminance component replacement processing for all the pixel blocks is completed, a new pixel block obtained by dividing the center pixel of the pixel block vertically, horizontally, or diagonally with a predetermined pixel shift is used. The photographic image processing method according to claim 1, wherein the process of executing the luminance component replacement process again is repeated a predetermined number of times.   3. The photographic image processing method according to claim 1, wherein the luminance filter processing step is executed on luminance component pixels indicating the maximum value and the minimum value extracted in the luminance replacement processing step. The luminance component image extraction step includes an RGB-YCbCr conversion processing step of converting an RGB color component of each pixel constituting the photographic image data into a luminance color difference component of YCbCr,
Color difference filter processing for generating color difference smoothed image data by filtering each color difference component image obtained in the RGB-YCbCr conversion processing step with a weighted average filter having a second filter size larger than the first filter size. Steps,
A YCbCr-RGB conversion processing step for inversely converting a luminance color difference component composed of the luminance component obtained in the luminance substitution processing step and the color difference component filtered in the color difference filter processing step into an RGB color component;
The photographic image processing method according to claim 1, further comprising:   5. The photographic image processing method according to claim 4, wherein a filter size larger than the block size for compression by JPEG is selected as the second filter size.   The weighted average filter has a large filter coefficient in the vicinity of a predetermined threshold value for determining whether or not the difference between the center pixel and the peripheral pixel within the filter size is zero or a contour portion of the image, and the filter coefficient is small enough to deviate from the threshold value. The photographic image processing method according to claim 1, wherein the filter is a filter dynamically determined according to target image data. A photographic image processing program for suppressing granular noise contained in photographic image data,
RGB-YCbCr conversion processing step of converting RGB color components of each pixel constituting the photographic image data into YCbCr luminance color difference components;
A luminance filter processing step for generating luminance smoothed image data by filtering the luminance component image obtained in the RGB-YCbCr conversion processing step with a weighted average filter of a first filter size;
Luminance replacement that divides the luminance component image into pixel blocks of a predetermined size and replaces the luminance component indicating the maximum value and the minimum value extracted from each divided region with the luminance component of the corresponding pixel of the luminance smoothed image data Processing steps;
Color difference filter processing for generating color difference smoothed image data by filtering each color difference component image obtained in the RGB-YCbCr conversion processing step with a weighted average filter having a second filter size larger than the first filter size. Steps,
A YCbCr-RGB conversion processing step for inversely converting a luminance color difference component composed of the luminance component obtained in the luminance substitution processing step and the color difference component filtered in the color difference filtering processing step into an RGB color component;
A photographic image processing program that causes a computer to execute. A photographic image processing apparatus that suppresses granular noise included in photographic image data,
An RGB-YCbCr conversion processing unit for converting RGB color components of each pixel constituting the photographic image data into luminance and color difference components of YCbCr;
A luminance filter processing unit that generates luminance smoothed image data by filtering the luminance component image obtained by the RGB-YCbCr conversion processing unit with a weighted average filter having a first filter size;
Luminance replacement that divides the luminance component image into pixel blocks of a predetermined size and replaces the luminance component indicating the maximum value and the minimum value extracted from each divided region with the luminance component of the corresponding pixel of the luminance smoothed image data A processing unit;
Color difference filter processing for generating color difference smoothed image data by filtering each color difference component image obtained by the RGB-YCbCr conversion processing unit with a weighted average filter having a second filter size larger than the first filter size. And
A YCbCr-RGB conversion processing unit that reversely converts a luminance color difference component composed of the luminance component obtained by the luminance replacement processing unit and the color difference component filtered by the color difference filter processing unit into an RGB color component;
A photographic image processing apparatus.