JP2008300981A - Image processor and processing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To increase a speed of color conversion processing on a motion image including a successive still image group. <P>SOLUTION: In a step S501, the motion image including the successive still image group is divided for each scene and in a step S502, the plurality of still images constituting the divided scenes are analyzed to detect movement amounts for each pixel of the scenes. In a step S503, a color matching result for a first still image of a scene is held in a cache. For second and succeeding still images, retrieval is carried out within cache retrieval ranges set based upon the movement amounts for each pixel and when cache data is not found, color matching is carried out, and when cache data is found, the cache data is used as a color matching result. Thus, caches different for each scene are used and the retrieval ranges are set according to the movement amounts of the pixels to achieve the high speed color conversion processing. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to an image processing apparatus and an image processing method, and more particularly to an image processing apparatus and an image processing method for performing high-speed color conversion processing on a moving image.

  In recent years, in addition to the spread of personal computers, the spread of image digitizing devices such as digital cameras and digital video has been remarkable. In addition, with the spread of highly functional applications such as CAD and CG software, not only high-end users but also general users can easily create moving image content. The created moving image content is used in many scenes such as a movie, a game, a television commercial, commercial content on the Web, and a presentation scene in an office environment.

  In addition, with the rapid spread of moving image content, development of image display devices such as high-precision projectors, monitors, and televisions for displaying such content is also remarkable at present. Along with this, there is an increasing demand for realizing the color matching technique that has been realized in the conventional still image also in the moving image.

  There are two types of moving image content: content that is made into a moving image file and content that is composed of continuous still images.

  In particular, the former video file content requires high-precision hardware that enables high-speed computation in order to realize high-speed processing of the extremely large amount of data, and high cost is inevitable. It was. Therefore, it has been difficult for general users to handle content in the form of moving image files.

  On the other hand, since the moving image content composed of the latter group of continuous still images can be basically processed in the same manner as the processing for still images, even a general user is relatively easy to handle. However, in order to apply digital processing to such moving image content including a group of continuous still images, the same digital is applied to each of a huge number of still image files of thousands to tens of thousands constituting the moving image content. It is necessary to repeat the process. Therefore, when the resolution of each still image is increased and the number of files constituting the content increases as the frame rate of the content increases, the processing time increases when the amount of data becomes enormous.

A color matching technique for reducing the processing speed has been proposed for still images (see, for example, Patent Document 1). According to the color matching technology relating to still images described in Patent Document 1, the value conversion process is performed with adjacent pixels, and when the cache is hit, the cache table is used to increase the speed of the color conversion process. is doing.
JP 2002-57910 A

  However, the color matching technique for still images as described in Patent Document 1 cannot be applied as it is to moving image content composed of a group of continuous still images. That is, in the case of a still image on the assumption that there is a motion, the adjacent pixels are hardly in the same state, so the possibility of hitting the cache is extremely low. Therefore, as a result, for still images constituting the moving image content, a color conversion processing calculation with a high load is performed on almost all pixels, and there is a problem that a reduction in processing time cannot be expected.

  The present invention has been made to solve the above-described problems, and provides an image processing apparatus and an image processing method capable of performing high-speed color conversion processing on a moving image composed of still image groups. Objective.

  As a means for achieving the above object, an image processing apparatus of the present invention comprises the following arrangement.

  That is, an image processing apparatus for processing a moving image composed of continuous still image groups, a scene dividing means for dividing the moving image into scenes, and a plurality of still images constituting the divided scene. Analyzing and for each pixel, image analysis means for detecting the amount of movement in the scene, color matching is performed on the first still image in the scene, and the value for each pixel as the color matching result is obtained. A cache generation unit that holds the cache, and a setting unit that sets a cache search range for each pixel based on the movement amount for each pixel detected by the image analysis unit for the second and subsequent still images in the scene And searching the cache search range in the cache for each pixel for the second and subsequent still images in the scene. And having a color matching means for performing color matching I.

  According to the present invention having the above-described configuration, high-speed color conversion processing can be performed on a moving image configured by a still image group.

  Hereinafter, the present invention will be described in detail based on preferred embodiments with reference to the accompanying drawings. The configurations shown in the following embodiments are merely examples, and the present invention is not limited to the illustrated configurations.

<First Embodiment>
FIG. 1 is a block diagram illustrating a configuration of an image processing apparatus according to the present embodiment. In the figure, reference numeral 101 denotes a personal computer (hereinafter referred to as a PC) to which a color monitor 124 is connected. The PC 101 includes an application storage unit 102, a scene division unit 103, an image cache generation unit 105, a color management processing unit 107, and an image processing unit 109. Then, a scene division information storage unit 104, an image cache storage unit 106, a color matching table storage unit 108, and a converted image storage unit 110 for storing data generated or used by the respective processing units are provided. Have. Further, it has a parameter storage unit 111 for storing various parameters. The parameter storage unit 111 includes an image number count storage unit 112, a threshold A storage unit 113, a threshold B storage unit 114, a threshold C storage unit 115, a scene number storage unit 116, and a scene division information array storage unit 117. Further, it includes a movement count storage unit 118, a pixel information storage unit 119, a cache storage unit 120, a search range storage unit 121, an input folder path storage unit 122, and an output folder path storage unit 123.

Outline of Color Matching Process Hereinafter, the overall flow of the color matching process in the image processing apparatus of the present embodiment will be described with reference to the flowchart of FIG. 2 and FIGS.

  First, in step S201 in FIG. 2, the image processing application stored in the application storage unit 102 is activated. FIG. 3 shows an example of a UI screen by the image processing application started here.

  In step S202, the user stores a folder (hereinafter referred to as an input folder) in which a continuous still image file group (hereinafter referred to as an input continuous still image group) that is a source of a moving image file to be converted is stored. ) Is specified. This designation is performed in the input folder setting unit 301 shown in FIG. 3, and the path of the designated input folder is stored in the input folder path storage unit 122.

  Here, the input continuous still images stored in the folder indicated by the input folder path are arranged so that the movements are continuous as shown in FIG. It is assumed that the image is composed of an image group (hereinafter referred to as a scene). For example, the example of FIG. 4 shows an input continuous still image group composed of three scenes: a scene in which a bird flies, a scene in which the moon moves, and a scene in which a bird falls.

  Next, in step S203, a folder (hereinafter referred to as an output folder) for storing a group of continuous still images after color matching processing (hereinafter referred to as an output continuous still image group) is designated from 302 in FIG. That is, the output continuous still image group that is the result of performing the color matching process on the input continuous still image group stored in the input folder designated in step S202 is stored in the output folder. The designated output folder path is stored in the output folder path storage unit 123.

  In step S204, a color matching table to be used when color matching processing is performed on the input continuous still image group is designated. This designation is completed in the matching table setting unit 303 shown in FIG. 3, and the designated color matching table is stored in the color matching table storage unit 108.

  In step S205, when the user presses the conversion button 304 shown in FIG. 3, color matching processing using the color matching table stored in the color matching table storage unit 108 is started for the input continuous still image group. The Note that the input continuous still image group to be processed is stored in the input folder specified by the input folder path stored in the input folder path storage unit 122. The output continuous still image group created by completing the color matching process is stored in a folder specified by the output folder path stored in the output folder path storage unit 123. The outline and details of the color matching process in step S205 will be described later.

  In step S206, when the user presses the end button 305 shown in FIG. 3, the color matching process in this embodiment is ended.

Color Matching Process Details FIG. 5 is a flowchart showing an outline of the color matching process in step S205 described above.

  First, in step S501, the input continuous still image group stored in the folder indicated by the folder path stored in the input folder path storage unit 122 is divided into n scenes. For example, an input continuous still image group as shown in FIG. 4 is divided into three scenes: a scene 1 in which a bird flies, a scene 2 in which the moon moves, and a scene 3 in which a bird falls as shown in FIG. Is done. Details of the scene division process in step S501 will be described later. The processes after scene division (S502, S503) are executed for all n scenes with the divided scene as a unit.

  In step S502, image analysis is performed on all images constituting the scene, and movement amounts of all pixels are detected in order to determine a cache search range in the color matching process performed in step S503 in the subsequent stage. Details of the image analysis processing in step S502 will be described later.

  In step S503, the cache search range in each scene is determined based on the pixel movement amount detected in step S502, and color matching processing is performed on all input still image groups constituting the scene. The output still image group obtained by the color matching process is stored in the folder indicated by the output folder path stored in the output folder path storage unit 123, and the process ends. Details of the color matching process in step S503 will be described later.

Scene Division Processing FIG. 7 is a flowchart showing details of the scene division processing in step S501 described above.

  First, in step S701, the number of scenes stored in the scene number storage unit 116 is initialized. In step S702, the image number count stored in the image number count storage unit 112 is initialized. Here, the image number count is a value indicating the number of the last continuous image in the scene that is in the input continuous still image group. In the example shown in FIG. The number of images in scene 2 is 8.

  In step S703, a histogram used for scene division calculation in the scene division unit 103 is created. In this embodiment, scene division processing using a histogram will be described, but division may be performed using any other method. Details of the histogram creation process in step S703 will be described later.

  In step S704, it is determined whether the image for which the histogram has been created is the first image in the input continuous still image group, that is, the first still image. If it is the first still image, the process proceeds to step S705. If it is the second or subsequent still image, the process proceeds to step S706.

  In step S705, the histogram created in step S703 is stored in the scene division information storage unit 104.

  On the other hand, in step S706, an error D from the histogram of the previous still image stored in the scene division information storage unit 104 is calculated as the amount of change in the histogram for each still image. Although the calculation method of the error D is arbitrary, as an example, the histogram created in step S703 and the area of the histogram of the previous still image stored in the scene division information storage unit 104 are respectively calculated. There is a method in which the difference in area is defined as error D.

  In step S707, the error D calculated in step S706 is compared with the threshold A stored in the threshold A storage unit 113. If the error D is greater than the threshold A, it is determined that the scene has been switched, and the process proceeds to step S708. move on. On the other hand, if the error D is less than or equal to the threshold A, it is determined that the scene has not been switched, and the process proceeds to step S705. Here, the value of the threshold A may be set in advance so as to be small when the number of scenes constituting the input still image group is large and large when the number of scenes is small.

  In step S708, the number of scenes stored in the scene number storage unit 116 is incremented. Specifically, the number of scenes stored in the scene number storage unit 116 is extracted, 1 is added to the number of scenes, and the number of scenes after the addition is stored in the scene number storage unit 116.

  In step S 709, the image count at the time when the scene is switched is registered in the image count storage unit 112 as an image count in the previous scene, that is, the scene corresponding to the number of scenes stored in the scene count storage unit 116. In the example shown in FIG. 6, when the scene 1 is switched to the scene 2, the image count for the scene 1 is registered as 4.

  In step S710, the image number count as a variable stored in the image number count storage unit 112 is incremented. Specifically, the number of images stored in the image number count storage unit 112 is extracted, 1 is added to the image number count, and the image number count after the addition is stored in the image number count storage unit 112 again. .

  In step S711, it is determined whether or not the scene division processing has been completed for all the still images constituting the input continuous still image group. If the scene division process has been completed for all still images, the scene division process is terminated. If not, the process proceeds to step S703 to start creating a histogram for the next still image.

Histogram Creation Process FIG. 8 is a flowchart showing details of the histogram creation process in step S703 described above. In FIG. 8, a case where the target image is an RGB image is shown as an example, but the same processing can be performed for an image composed of other elements.

  First, in step S801, the histogram arrays R [255], G [255], and B [255] stored in the scene division information array storage unit 117 are initialized. In step S802, pixel data (Rd, Gd, Bd) of a still image for creating a histogram is acquired.

  In step S803, 1 is added to the histogram array R [Rd] having the R color density value acquired in step S802 as the index Rd. For example, when the density value of R color acquired in step S802 is 100, an addition process of R [100] = R [100] +1 is performed. Similarly, in steps S804 and S805, the G color and B color are respectively added to the histogram array similar to the R color.

  In step S806, it is determined whether or not the histogram creation process has been completed for all the pixel data of the still image. If all the pixel data has been completed, the process ends. If not, the process proceeds to step S802. Return.

  Here, FIG. 9 shows an example of an R color histogram among the primary colors (RGB in this case) generated by the histogram creation processing shown in FIG. The histogram shown in FIG. 9 indicates (0, R [0]),..., (255, R [255]) where the first element represents the density value and the second element represents the number of pixels having the density value. It is a bar graph.

● Image analysis processing (detection of pixel movement)
FIG. 10 is a flowchart showing image analysis processing for determining the cache search range of each scene in step S502 described above. The process shown in the flowchart of FIG. 10 is performed for each of the scenes divided in step S501, analyzes the movement of each pixel in the scene, and determines the final movement amount in the scene for each pixel. To detect.

  First, in step S1001, the movement count stored in the movement count storage unit 118 is initialized. Here, the movement count is a value indicating the magnitude of the movement amount of each pixel in the scene, and is held for all the pixels constituting the first image in the scene. In steps S1002 to S1006, the movement count for each pixel is determined by analyzing all the images constituting the scene.

  In step S1002, it is determined whether or not the still image that is the target of image analysis is the first scene. This determination is performed by referring to the image number count registered for each scene in the image number count storage unit 112. If it is determined that the still image is the first image of the scene, the process proceeds to step S1003. If the still image is not the first image of the scene, that is, the second or later image, the process proceeds to step S1004.

In step S <b> 1003, a threshold value B for determining the movement amount of the pixel associated with each coordinate in the first still image is determined and stored in the threshold value B storage unit 114. That is, the threshold value B is set for each coordinate in the first still image. Here, as a method for determining the threshold B, for example, in the case of an RGB image, the pixel information (R _{i, j} , G _{i, j} , B _{i, j} ) of the coordinates (i, j) in the first still image is used. On the other hand, a predetermined change amount is set. For _{example, (R i, j -10,} G i, j -10, B i, j -10) _{or, (R i, j + 10} , G i, j + 10, B i, j +10) as of the The threshold B may be a value obtained by adding or subtracting the change amount 10 to the pixel.

  On the other hand, in step S1004, the pixel information of each coordinate is compared with the threshold value B created in step S1003. If the pixel information is larger than the threshold B as a result of the comparison, it is determined that the pixel has a large movement from the top image of the scene, and the process proceeds to step S1005. Determines that the movement is small, and proceeds to step S1006.

  In step S1005, the movement count is incremented because the movement of the pixel is large. Specifically, the movement count stored in the movement count storage unit 118 is taken out, 1 is added to the movement count, and the movement count after the addition is stored in the movement count storage unit 118.

  In step S1006, it is determined whether or not the movement count calculation processing for the pixel has been completed for all the still images constituting the scene. If the movement count calculation processing has been completed for all the still images, the process proceeds to step S1007. If not completed yet, the process proceeds to step S1002 in order to perform processing for the next still image.

  Next, in steps S1007 to S1009, the amount of change is determined for each pixel based on the movement count for each pixel determined as described above.

  First, in step S <b> 1007, it is determined whether or not the movement count for each pixel is larger than a threshold value C that is an arbitrary constant stored in the threshold value C storage unit 115. If the movement count is greater than the threshold C, it is determined that the pixel has a large movement in the scene, and the process proceeds to step S1008. On the other hand, if the movement count is less than or equal to the threshold value C, it is determined that the pixel has little movement in the scene, and the process proceeds to step S1009.

  In step S1008, information indicating that the pixel is a dynamic pixel having a large change amount is registered in the pixel information storage unit 119 as pixel information. On the other hand, in step S1009, the fact that the pixel is a static pixel with a small amount of change is registered in the pixel information storage unit 119 as pixel information.

  The determination of the movement count for each pixel and the registration of the change amount performed in steps S1001 to S1009 are performed for all the pixels in the first still image in the scene. Based on the amount of change of each pixel registered here, a cache search range referred to in the color matching process described later is determined.

  In step S1010, whether or not dynamic or static pixel determination has been completed for all pixels to which the movement count is assigned in step S1001 (that is, all pixels in the first still image in the scene). Determine. If completed, the process ends. If not completed, the process moves to step S1001 to determine the next pixel.

Color Matching Process FIG. 11 is a flowchart showing details of the color matching process in step S503 described above. The process shown in the flowchart of FIG. 11 is performed for each of the scenes divided in step S501.

  First, in step S1101, it is determined whether or not the still image to be color-matched is the first image in the scene. This determination is performed by referring to the image number count registered for each scene in the image number count storage unit 112. If it is the first image, the process advances to step S1102 to perform color matching processing on all pixel information and create cache data. On the other hand, if it is not the first sheet, that is, the second sheet or later, the process advances to step S1106 to perform color matching processing with reference to the cache data.

  First, the color matching process for the first still image in the scene will be described.

  In step S1102, the color management processing unit 107 performs a color matching operation using the color matching table stored in the color matching table storage unit. Here, the color matching calculation is a process of calculating the RGB value of the output pixel that enables desired color reproduction with respect to the RGB value of the input pixel, as shown in FIG. A specific color matching method may be arbitrary.

  In step S1103, the image cache generation unit 105 registers the color matching result performed in step S1102 in the image cache storage unit 106 as cache data. If the image cache stored in the image cache storage unit 106 is an RGB image, for example, as shown in FIG. 12, the image cache is composed of coordinate information, input RGB data, and output RGB data calculated in step S1102. To do.

  In step S1104, the image processing unit 109 stores the color-matched pixel data in the converted image storage unit 110.

  In step S1105, it is determined whether or not the color matching process has been completed for all the pixels in the first image. If the color matching process has been completed for all the pixels, the process proceeds to step S1114. If the color matching process has not been completed, the process proceeds to step S1102 to perform the process for the next pixel.

  Next, color matching processing using cache data for the second and subsequent still images in the scene will be described.

  In step S1106, based on the pixel information stored in the pixel information storage unit 119, it is determined whether the pixel data that is the color matching target is a static pixel or a dynamic pixel. If it is a static pixel, the process proceeds to step S1107, and if it is a dynamic pixel, the process proceeds to step S1108.

  In step S 1107, the cache search range is set to an arbitrary region S and stored in the search range storage unit 121. On the other hand, in step S 1108, the cache search range is set to an arbitrary region L and stored in the search range storage unit 121. The areas S and L set as the cache search range are different values depending on the scene, and there is a relationship of S <L. That is, the search area L for dynamic pixels is set to be wider than the search area S for static pixels.

  In step S1109, it is determined whether or not cache data for the pixel data to be subjected to color matching processing is stored in the cache storage unit 120. In this determination, in the cache data stored in the cache storage unit, first, it is verified whether or not a data value (input RGB value) of the pixel is set at a position corresponding to the coordinates of the pixel. If it is not set, the pixel has moved, and therefore, it is verified whether or not the data value of the pixel exists in the cache data within the search range set as described above. That is, the search in the cache data is performed using the area S or the area L stored in the search range storage unit 121 in step S1107 or S1108 as the search range.

  In step S1109, if cache data exists within the search range, the process proceeds to step S1110. If cache data does not exist, the process proceeds to step S1111.

  In step S1110, the image processing unit 109 stores the color-matched pixel data in the converted image storage unit 110. At this time, if the cache data exists in step S1109, the value of the cache data is stored. If the cache data does not exist, the pixel data obtained as a color matching result in step S1111 described later is stored. Stores a value.

  In step S <b> 1111, the color management processing unit 107 performs the same color matching process as in step S <b> 1102 described above. In step S <b> 1112, the image cache generation unit 105 updates the cache data by overwriting the matching calculation result in step S <b> 1111 on the cache data of the same coordinates stored in the image cache storage unit 106.

  In step S1113, it is determined whether or not the color matching process referring to the cache data for all the pixels has been completed. If the color matching process for all the pixels has been completed, the process proceeds to step S1114. If the color matching process has not been completed, the process proceeds to step S1106 to process the next pixel.

  As described above, the color matching process corresponding to the order in the scene is completed for one still image. In step S1114, the image processing unit 109 stores the color-matched pixel data stored in the converted image storage unit 110 as an image file. At this time, the image file is stored in a folder indicated by the output folder path stored in the output folder path storage unit 123.

  In step S1115, it is determined whether or not color matching has been completed for all still images constituting the scene. If the color matching has been completed for all still images, the process ends. If not, the process advances to step S1101 to perform color matching on the next still image.

  As described above, according to the present embodiment, the group of still images constituting the moving image content is divided into scenes based on the amount of change in the feature amount in each still image, and a color using a different cache for each scene. Perform the matching process. At this time, by changing the cache search range in accordance with the magnitude of the movement, a higher-speed color matching process can be performed.

<Other embodiments>
Although the embodiment has been described in detail above, the present invention can take an embodiment as a system, apparatus, method, program, recording medium (storage medium), or the like. Specifically, the present invention may be applied to a system composed of a plurality of devices (for example, a host computer, an interface device, an imaging device, a web application, etc.), or may be applied to a device composed of a single device. good.

  In the present invention, a software program for realizing the functions of the above-described embodiments is supplied directly or remotely to a system or apparatus, and the computer of the system or apparatus reads and executes the supplied program code. Is also achieved. The program in this case is a computer-readable program that corresponds to the flowchart shown in the drawing in the embodiment.

  Accordingly, since the functions of the present invention are implemented by computer, the program code installed in the computer also implements the present invention. In other words, the present invention includes a computer program itself for realizing the functional processing of the present invention.

  In this case, as long as it has a program function, it may be in the form of object code, a program executed by an interpreter, script data supplied to the OS, or the like.

  Recording media for supplying the program include the following media. For example, floppy disk, hard disk, optical disk, magneto-optical disk, MO, CD-ROM, CD-R, CD-RW, magnetic tape, nonvolatile memory card, ROM, DVD (DVD-ROM, DVD- R).

  As a program supply method, the following method is also possible. That is, the browser of the client computer is connected to a homepage on the Internet, and the computer program itself (or a compressed file including an automatic installation function) of the present invention is downloaded to a recording medium such as a hard disk. It can also be realized by dividing the program code constituting the program of the present invention into a plurality of files and downloading each file from a different homepage. That is, a WWW server that allows a plurality of users to download a program file for realizing the functional processing of the present invention on a computer is also included in the present invention.

  In addition, the program of the present invention is encrypted, stored in a storage medium such as a CD-ROM, distributed to users, and key information for decryption is downloaded from a homepage via the Internet to users who have cleared predetermined conditions. It is also possible to make it. That is, the user can execute the encrypted program by using the key information and install it on the computer.

  Further, the functions of the above-described embodiments are realized by the computer executing the read program. Furthermore, based on the instructions of the program, an OS or the like running on the computer performs part or all of the actual processing, and the functions of the above-described embodiments can also be realized by the processing.

  Further, the program read from the recording medium is written in a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer, and then executed, so that the program of the above-described embodiment can be obtained. Function is realized. That is, based on the instructions of the program, the CPU provided in the function expansion board or function expansion unit can perform part or all of the actual processing.

It is a block diagram which shows the structure of the image processing apparatus in one Embodiment which concerns on this invention. It is a flowchart which shows the whole color matching process in this embodiment. It is a figure which shows the example of a user interface in this embodiment. It is a figure which shows an example of the moving image group in this embodiment. It is a flowchart which shows the outline | summary of the color matching process in this embodiment. It is a figure which shows the example of a scene division | segmentation of the moving image group in this embodiment. It is a flowchart which shows the scene division | segmentation process in this embodiment. It is a flowchart which shows the histogram creation process in this embodiment. It is a figure which shows the histogram example of the primary color produced in this embodiment. It is a flowchart which shows the image analysis process in this embodiment. It is a flowchart which shows the detail of the color matching process in this embodiment. It is a figure which shows the example of an image cache in this embodiment.

Claims (9)

An image processing apparatus for processing a moving image composed of continuous still image groups,
Scene dividing means for dividing the moving image into scenes;
Image analysis means for analyzing a plurality of still images constituting the divided scene and detecting a movement amount in the scene for each pixel;
A cache generating means for performing color matching on the first still image in the scene and holding a value for each pixel as a result of the color matching as a cache;
Setting means for setting a cache search range for each pixel based on the movement amount for each pixel detected by the image analysis means for the second and subsequent still images in the scene;
Color matching means for performing color matching by searching the cache search range in the cache for each pixel for the second and subsequent still images in the scene;
An image processing apparatus comprising:   The image processing apparatus according to claim 1, wherein the scene dividing unit divides the still image group into a plurality of scenes based on a change amount of a histogram for each still image.   The image processing apparatus according to claim 1, wherein the image analysis unit detects whether or not there is a movement exceeding a predetermined movement amount in a scene for each pixel.   4. The color matching unit according to claim 1, wherein when the cache data corresponding to the pixel is detected in the cache search range, the color matching unit uses the cache data as a color matching result for the pixel. The image processing apparatus according to item 1.   The image processing apparatus according to claim 4, wherein the color matching unit performs color matching on the pixel when cache data corresponding to the pixel is not detected in the cache search range.   The said color matching means updates the said cache with the result of having performed the color matching with respect to this pixel, when the cache data corresponding to the said pixel are not detected in the said cache search range. Image processing device. An image processing method for processing a moving image composed of continuous still image groups,
A scene dividing step in which the scene dividing means divides the moving image for each scene;
An image analysis step for analyzing a plurality of still images constituting the divided scene and detecting a movement amount in the scene for each pixel;
A cache generation step, wherein the cache generation means performs color matching on the first still image in the scene, and stores a value for each pixel as the color matching result as a cache;
A setting step for setting a cache search range for each pixel based on a movement amount for each pixel detected in the image analysis step for the second and subsequent still images in the scene;
A color matching step in which color matching means performs color matching on the second and subsequent still images in the scene by searching the cache search range in the cache for each pixel;
An image processing method comprising:   A computer program that, when executed on a computer, causes the computer to function as the image processing apparatus according to any one of claims 1 to 6.   A computer-readable recording medium on which the computer program according to claim 8 is recorded.

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