JP2011138393A - Image processor and image processing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To reduce the computational complexity for converting a color space when transparently combining a large-volume spectral image with another image, by solving the conventional method of transparently combining superimposed object images, which requires color space conversion. <P>SOLUTION: The image processor is configured to determine a color space of each of input object images to be transparently combined (S403, F404), and to, when the color space is a LabPQR color space, convert the LabPQR color space into an RGB color space by using only Lab components without using any PQR component showing spectral information components (S405), and to transparently combine, when the conversion of all object images into the RGB color space ends, the object images (S409). <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to an image processing apparatus and an image processing method for performing transparent composition processing on a region where a plurality of object images overlap.

  When an output image obtained by photographing a subject with a camera and outputting it with a printer is compared with an original subject, the appearance may be the same under a certain ambient light, but the appearance may be different under another ambient light. This phenomenon is called metamerism, and is caused by the difference between the spectral reflectance of the subject and the spectral reflectance of the output image. In recent years, a method has been proposed for solving metamerism by capturing a subject with a multiband camera, obtaining its spectral reflectance as spectral information, and performing output according to the spectral information using a printer equipped with special color ink. Has been.

  However, the spectral information has a problem that the data amount is remarkably increased as compared with the color information obtained by color reproduction using the conventional tristimulus values. In order to solve this problem, a method of compressing spectral information using a 6-dimensional LabPQR color space has been proposed (see Non-Patent Document 1). Since the LabPQR color space includes the basic stimulus value L * a * b * components, the LabPQR color space has a feature that it is easy to handle even for users who do not require spectroscopic information. Hereinafter, the basic stimulus value L * a * b * is described as Lab as necessary.

  As a use case of an image including such spectral information (hereinafter referred to as a spectral image), for example, reproduction of a cultural heritage such as a painting can be considered. In such a use case, it is desirable to use spectral information because metamerism can occur when a cultural heritage is replicated using only basic stimulus values acquired by a normal camera.

  FIG. 11 is a diagram showing a main processing flow when spectral information of cultural heritage acquired by a multiband camera is once compressed into LabPQR, printed by a special color ink printer, and copied. The spectral information 1102 acquired by the multiband camera 1101 is compressed into an image 1104 represented by LabPQR by the spectral information compression processing 1103. An image 1104 represented by LabPQR is converted into color material amount data 1106 by a color material amount data conversion process 1105. The color material amount data 1106 is printed by the special color ink printer 1107. LabPQR is advantageous when transferring or storing data because the amount of data is smaller than that of uncompressed spectral information.

  Another possible use case for spectral images is to print product catalogs. Here, consider a case where a curtain is ordered by looking at a catalog of mail order sales. In such a case, in the current color reproduction system using tristimulus values, the color on the catalog and the color that the purchaser sees when the actual curtain is used in the ambient light are different. Sometimes.

  In order to solve such a color difference between the catalog and the actual product, a spectral image of the curtain acquired by the multiband camera may be printed as a catalog photo. As a result, the catalog photograph has substantially the same spectral reflectance as the actual curtain, so that the color of the curtain can be confirmed by viewing the catalog under the ambient light that the purchaser actually uses.

  The flow of processing in such a catalog creation system is as follows, for example. First, a spectral image is acquired by a multiband camera, and print data is created by processing the spectral image together with computer graphics and characters using an editing application. The print data is converted into color material amount data by a RIP (Raster Image Processor), and the color material amount data is printed by a special color ink printer. In contrast to cultural heritage reproduction, catalog print data includes computer graphics, text, etc. in addition to spectral images, and therefore requires a more advanced RIP. Hereinafter, elements such as images, computer graphics, and characters included in the print data are collectively referred to as object images.

M. Derhak, M. Rosen, "Spectral Colorimetry Using LabPQR-An Interim Connection Space". "Color Imaging Conference 2004" USA, Imaging Science and Technology, 2004.Nov.page246-250

  When the spectral image is represented by the above-described LabPQR, the RIP can handle the spectral image as a simple multi-channel image. However, even though it is compressed, LabPQR has 6 channels, and considering that a normal image has 3 or 4 channels, the amount of data handled will increase considerably.

  Here, a transparent composition process for a region where a plurality of object images overlap is considered. In the transparent composition process in the RIP, it is necessary to convert the colors to be transparently combined into the same color space, and normally the transparent composition is performed in RGB. Therefore, when performing transmission composition processing on a spectral image represented by LabPQR, it is necessary to convert the color space of the spectral image from LabPQR to RGB, and the amount of calculation becomes enormous.

  However, it is considered that a user who performs a transmission / combination process on a spectral image no longer seeks a characteristic of the spectral image that can reproduce a color close to the real object regardless of ambient light. Therefore, in the conventional transmission composition processing for spectral images, it is sufficient if the color reproduction accuracy using the basic tristimulus values is obtained, but it is necessary to perform a huge amount of calculation including spectral information. It was.

  The present invention has been made to solve the above-described problems, and the amount of calculation can be reduced when an image expressed using the spectral reflectance of a subject is subjected to a transmission composition process with another image. An object of the present invention is to provide an image processing apparatus and an image processing method.

  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 that transmits and combines other images with respect to an image of the subject expressed using spectral information indicating the spectral reflectance acquired at the time of shooting of the subject, and includes a plurality of images to be combined. A color space determination unit that determines whether or not a color space that represents an image is a first color space that includes a basic component that indicates a stimulus value and an additional component that indicates spectral information; Among the images, an image determined by the color space determination unit to be expressed in the first color space is converted into the second color space using only the value of the basic component in the first color space. First color space conversion means for converting into an image to be expressed; and, among the plurality of images, an image determined by the color space determination means as not being expressed in the first color space Change to an image expressed in the color space of Second color space converting means for combining, and the plurality of images converted into the second color space by the first and second color space converting means for transparent composition on the second color space And means.

  According to the present invention having the above-described configuration, when the image expressed using the spectral reflectance of the subject is subjected to the transmission composition process with another image, the amount of data to be color space converted is reduced, and the calculation is performed. The amount can be greatly reduced.

The figure which shows the system configuration | structure in 1st Embodiment. The block diagram which shows the function structure in 1st Embodiment, The block diagram which shows the function structure in the drawing part of 1st Embodiment, The flowchart which shows the transparent composition process in 1st Embodiment, The figure which shows the example of a division | segmentation of the object which mutually overlapped in 1st Embodiment. The figure which shows the data structure of each object before the division | segmentation in 1st Embodiment, The figure which shows the data structure of each object after the division | segmentation in 1st Embodiment, The figure which shows the process outline | summary with respect to each area | region after the division | segmentation in 1st Embodiment, The figure which shows the data structure of the object after color space conversion in 1st Embodiment. The figure which shows the example of the display message in 1st Embodiment. It is a figure which shows the main processes of the printing system using a multiband camera and a special color ink printer.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. The following embodiments do not limit the present invention related to the scope of claims, and all combinations of features described in the present embodiments are essential to the solution means of the present invention. Not necessarily.

<First Embodiment>
In the present embodiment, another image is transparently combined with the image of the subject expressed using the spectral information indicating the spectral reflectance acquired at the time of photographing the subject. FIG. 1 is a block diagram showing a configuration of an image processing system to which the present embodiment is applied. In the figure, 101 is a central processing unit (CPU), 102 is a main storage device (main memory), and 103 is an auxiliary storage device (for example, a hard disk). Reference numeral 104 denotes an input device (eg, mouse, keyboard, printer control panel), 105 denotes a display device (eg, display, liquid crystal panel), 106 denotes an image forming apparatus (printer engine), and 107 denotes a bus. The auxiliary storage device 103 stores a program and data including a printer driver. These programs and data are appropriately read into the main storage device 102 through the bus 107 and executed by the CPU 101 under the control of the CPU 101 based on signals from the input device 104. Note that the transparent composition processing in this embodiment is performed by a printer driver. A print preview or the like is displayed on the display device 105 as appropriate. Depending on the signal from the input device 104, the data stored in the main storage device is sent to the image forming device 106 through the bus 107 and printed.

  FIG. 2 is a diagram showing a functional configuration for performing printing processing according to the present embodiment, that is, processing for rasterizing generated print data by a printer driver and printing. First, the print data 206 generated by the print data generation unit 205 is interpreted by the print data interpretation unit 207. On the other hand, the operation content input from the input unit 201 to the driver UI input unit 202 (UI: User Interface) is passed to the print data interpretation unit 207 as print settings. The processing result corresponding to the operation content input to the driver UI input unit 202 is appropriately reflected in the driver UI output unit 203 and output to the display unit 204. The drawing command generated by the print data interpretation unit 207 is passed to the drawing unit 208 and rendered. Color material amount data 209 that is a rendering result output from the drawing unit 208 is sent to the output unit 210 and printed.

  FIG. 3 is a diagram showing a main functional configuration in the drawing unit 208 in FIG. The drawing command generated by the print data interpretation unit 207 is passed to the object selection unit 301. The object selection unit 301 selects an object image (hereinafter referred to as an object) that requires a transparent composition process in the drawing command. The selected individual object is divided into regions by the region dividing unit 302. The color space determination unit 303 is a part that determines a color space for a necessary region. The color space conversion unit 304 is a part that performs color space conversion on a necessary object based on the determination result in the color space determination unit 303. The notification processing unit 305 is a part that outputs a message to the driver UI output unit 203 in order to notify that when a specific color space conversion is performed by the color space conversion unit 304. The transparent composition processing unit 306 is a part that performs transparent composition of a plurality of objects expressed in the same color space. The data conversion unit 307 is a part that converts image data expressed in a predetermined color space into color material amount data 209 that indicates the amount of color material used during printing.

  Hereinafter, the rendering process with the transparent composition process in the rendering unit 208 will be described in detail with reference to the flowchart of FIG.

  First, in S401, the object selection unit 301 selects an object to be combined. In the present embodiment, an example is given in which two objects that partially overlap each other are selected. For example, as shown in FIG. 5A, a case where a transparent graphic object overlaps an opaque spectral image object that includes spectral information in its data structure will be described below.

  In step S402, the area dividing unit 302 divides the object and extracts an overlapping area where a plurality of objects overlap. FIG. 5B shows an example of division and extraction here. That is, as shown in the figure, when the transparent graphic object 502 overlaps the opaque spectral image object 501, these two objects are divided into three areas 503, 504, and 505. Of these, 504 is an overlapping region where the spectral image object 501 and the graphic object 502 overlap.

  Here, the division of the overlapping region of the object in the present embodiment will be described in detail.

  First, two objects to be subjected to the transparent composition process, that is, the spectral image object 501 and the graphic object 502 are represented by a data structure as shown in FIG. 6, for example. FIG. 6A is a diagram showing an edge configuration of an object. Here, the edge is a set of points at which the scanning line along the x-axis direction intersects with the contour line of the object, and is represented, for example, as a linearly approximated point sequence (E1 to E4).

  FIG. 6B is a diagram illustrating an example of the data structure of the spectral image object 501. In the figure, Name is the name of an object, which is Object1 in this example. Edge is a set of edges forming the object, and the spectral image object 501 is formed by E3 and E4 as is apparent from FIG. Level indicates the depth of the object, and the smaller number indicates that the object is in the back. In this case, since Level is 0, the spectral image object 501 is treated as the deepest object. FillType is a method of filling an object. Since the spectral image object 501 is filled with a spectral image, it is expressed as ImageFill. FillImage is a pointer to the image to be filled. In the spectral image object 501, this is Image1. The pointer indicated by FillImage will be described later in detail with reference to FIG. FillImageTrasformMatrix indicates an affine transformation matrix for scaling, rotating, transforming, and moving an image. This affine transformation matrix indicates which pixel in the output raster image each pixel of the original image is mapped to. Yes. Alpha indicates the transparency set for the object. Since the spectral image object 501 is opaque, 1 is set. The transparency Alpha is represented by a value between 0 indicating complete transmission and 1 indicating non-transmission.

  FIG. 6C is a diagram showing an example of the data structure of Image1 set as a pointer to the image to be filled in FillImage. In the figure, Name is the name of the image to be filled. Type represents the color space of the image to be filled, and since Image1 for painting the spectral image object 501 is a spectral image, it is LabPQR. nChannel is the number of channels in the color space, and LabPQR is 6 channels. BitDepth indicates how many bits each channel is represented, and Width and Height represent the number of horizontal pixels and the number of vertical pixels, respectively. Data is actual RAW data of the image to be filled (Image1), and the LabPQR value of each pixel is stored in order.

  FIG. 6D shows an example of the data structure of the graphic object 502. Name, Edge, Level, and FillType are the same as in FIG. 6B described above. For example, in the edge, the graphic object 502 is formed by E1 and E2 shown in FIG. 6A, and the graphic object 502 is in front of the spectral image object 501, so the level is 1. FillType is FlatFill because the graphic object 502 is uniformly painted with the same color. FillColorType indicates the color space of the color to be painted, and is RGB in the graphic object 502. FillcolorNChannel is the number of channels in the color space. FillColorBitDepth indicates how many bits each channel is represented. FillColorData is the color value to fill. Alpha is the transparency set for the object, and since the graphic object 502 is transparent, it is represented here as 0.5.

  When the spectral image object 501 and the graphic object 502 having the data structure shown in FIG. 6 are divided as shown in FIG. 5B in S402 of FIG. 4, the respective data structures are as shown in FIG. Change.

  First, FIG. 7A shows an edge configuration after division, and it can be seen that E1 in FIG. 6A is divided into E5 and E6, and E4 is divided into E7 and E8, respectively.

  The spectral image object 501 is divided into regions 503 and 504 as shown in FIG. 5B, and the data structure of each region is shown in Object 3 shown in FIG. 7B and FIG. 7C. Object4. On the other hand, the graphic object 502 is divided into areas 504 and 505, and the data structure of each area is Object5 shown in FIG. 7 (d) and Object6 shown in FIG. 7 (e). Hereinafter, the data structure of each divided area is referred to as a divided object.

  FIG. 7B shows a divided object (Object 3) for the region 503 obtained by dividing the spectral image object 501, and each item is the same as that described in FIG. 6B. As shown in FIG. 7A, Edge represents an area 503 with E3 and E6 + E8. The E6 + E8 notation represents the edge that connects E6 and E8. Similarly, FIG. 7C shows a divided object (Object 4) for the region 504 into which the spectral image object 501 is divided. In these Object3 and Object4, the spectral image of Image1 is also set as an object to be filled with FillImage.

  FIG. 7D shows a divided object (Object 5) for an area 505 obtained by dividing the graphic object 502, and each item is the same as that described in FIG. 6D. FIG. 7E shows a divided object (Object 6) for an area 504 obtained by dividing the graphic object 502. FIG.

  That is, in S402, when a plurality of divided objects exist for a common area (Edge), this area is extracted as an overlapping area. According to the division example shown in FIG. 5, since the values of Edge are the same for Object4 and Object6 shown in FIGS. 7C and 7E, the region 504 corresponding to the Edge (E6 and E7) overlaps. Extracted as a region.

  Here, FIG. 8 shows an outline of processing in the present embodiment for each divided area. For example, since the region 503 is a non-transparent spectral image object, data in the LabPQR color space is directly converted into color material amount data. Further, since the area 505 is a transparent graphic object, it is transparently combined with the background and then converted into color material amount data. Then, the overlapping region 504 composed of two objects is subjected to the transparent composition process (S403 to S409 in FIG. 4), which is a feature of the present embodiment, and then converted into color material amount data.

  Hereinafter, the transmission composition processing (S403 to S409) in the present embodiment for the overlapping region extracted in S402 will be described.

  In S403, in the color space determination unit 303, for one of a plurality of divided objects (hereinafter referred to as the object of interest) for the overlapping area extracted in S402, whether or not the color space is a color space for performing transparent composition, Determine whether it is RGB. In this embodiment, the transmission composition is performed on the RGB color space, but, of course, it may be performed on another color space (for example, CMYK, Lab, XYZ, etc.). If the color space of the object of interest is RGB, the processing for the object of interest ends. If not, the process proceeds to S404, and LabPQR where the color space of the object of interest is the first color space including spectral information Judge whether there is. Note that, as described above, the LabPQR color space is composed of the basic component Lab indicating the stimulus value and the additional component PQR indicating the spectral information.

  As a result of the color space determination, if the color space is LabPQR, the process proceeds to S405 and the first color space conversion is performed. That is, in S405, the color space conversion unit 304 uses the basic component Lab only for the object of interest expressed in the LabPQR color space without using the additional component PQR, and is the second color space for composition. Convert to RGB color space. At this time, the conversion flag indicating that the conversion to the RGB color space has been performed without using PQR is turned ON. On the other hand, if the color space is not LabPQR, the second color space conversion is performed in S406. That is, in S406, the color space conversion unit 304 converts the color space of the object of interest that is not LabPQR into the RGB color space that is the second color space for synthesis by a normal method.

  Note that the color space of the object of interest can be easily determined by referring to FillType, FillImage, FillColorType, etc. in the data structure of the area. For example, in the present embodiment, Object4 and Object6 exist as divided objects for the overlapping region 504. For Object4, its FillType is ImageFill, and FillImage indicates Image1. Therefore, the color space of Object4 is determined to be LabPQR from the data of Image1. For Object6, since its FillType is FlatFill and FillColorType is RGB, the color space is determined to be RGB. Therefore, since the color space of Object4 is LabPQR, it is converted to RGB without using PQR in S405. On the other hand, since the color space of Object6 is originally RGB, conversion processing is not performed by the determination in S403.

  Here, the color space conversion from LabPQR to RGB in S405 will be described. For example, in the present embodiment, assuming that transmission composition is performed in the sRGB space, conversion from LabPQR to sRGB without using PQR is performed as follows. First, LabPQR is converted to Lab. For example, if (L, a, b, P, Q, R) = (L0, a0, b0, P0, Q0, R0), it is converted as (L, a, b) = (L0, a0, b0) . That is, each Lab value itself included in LabPQR is used. Then, conversion from the obtained Lab to XYZ is performed, and finally, conversion from XYZ to sRGB is performed.

  Note that the color space for transparent composition need not be sRGB, and may be a device RGB unique to the printer, for example. In this case, conversion to the device RGB may be performed by referring to a LUT (Look Up Table). For example, if this LUT inputs (L, a, b) = (44, 69, 60), all the correspondences such as (R, G, B) = (204, 0, 0) are output. Or a three-dimensional table prepared for a typical combination of L, a, and b. The LUT can be created by measuring the color patch actually output from the printer. When the Lab value to be obtained does not exist as a table element, such as when using a LUT having a representative Lab value, an interpolation operation using values before and after that may be applied.

  In addition, the conversion method to RGB in S405 is not limited to a method that does not use PQR at all, and a method that uses conversion so as to reduce the data amount of PQR is also applicable. For example, a fixed value such as (0,0,0) or (255,255,255) may be set as the PQR of LabPQR, and conversion may be performed from LabPQR to RGB with reference to a 6-dimensional LUT. Further, the conversion from LabPQR to RGB may be performed by a 6-dimensional LUT using a value obtained by converting each value of PQR into one of a plurality of reference values, for example, a value obtained by rounding off to the first decimal place.

  As described above, in this embodiment, the color space conversion from LabPQR to RGB is performed for Object4, but what is actually converted is the divided object of Image1 that represents the spectral image indicated by the FillImage. FIG. 9 shows a data structure after the color space of Image1 is converted from LabPQR to RGB. Each item is the same as that described with reference to FIG. 6 (c), but according to FIG. 9, Type changes from LabPQR to RGB and nChannel also changes from 6 to 3 with respect to FIG. 6 (c). Yes. It can also be seen that Data is converted to RGB color space for each pixel.

  As described above, when the color space conversion to RGB is completed for the object of interest, it is determined in S407 whether or not the processing of S403 to S406 has been completed for all the divided objects for the overlapping area extracted in S402. If completed, the process proceeds to S408, but if not completed, the process returns to S403 with the unprocessed divided object as the object of interest. Here, an example in which the color space conversion process is performed on one overlapping area is shown. However, if there are a plurality of overlapping areas extracted in S402, the color space according to S403 to S406 is naturally applied to each overlapping area. Conversion can be performed. Then, when the processing for all the overlapping regions is completed, the process proceeds to S408.

  In S408, if color space conversion that does not use PQR is performed in S405, the notification processing unit 305 notifies the user that processing has been performed without using spectral information. This notification may be made based on whether or not the conversion flag is turned on in S405. FIG. 10 shows an example of a pop-up message displayed on the display device 105 as the conversion notification. According to the figure, the page number being printed is shown, and the user is notified that there is a part where the spectral information has been dropped during the transmission composition process. If the conversion in S405 is not performed, the notification itself is not performed, or only the print page is displayed as shown in FIG.

  Next, in S409, the transmission composition processing unit 306 performs the transmission composition processing for the overlapping region 504 extracted in S402 in the second color space, that is, the RGB color space. This transmission composition processing is performed as follows. For example, the RGB value of the pixel corresponding to the spectral image object 501 in the overlapping region 504 is (Rb, Gb, Bb), and the RGB value of the pixel corresponding to the graphic object 502 is (Rf, Gf, Bf). Further, if the Alpha value indicating the transparency set in the graphic object 502 is α, the value after synthesis, that is, the RGB value (R, G, B) of the synthesized image is calculated as follows.

R = α × Rf + (1-α) × Rb
G = α × Gf + (1-α) × Gb
B = α × Bf + (1-α) × Bb
In S410, the data conversion unit 307 converts the RGB value of the composite image calculated as the composite result in S409 into color material amount data for printing. In this embodiment, since the color space after the transmission composition calculation is RGB, conversion from RGB values to color material amount data may be performed using a LUT given in advance. The LUT used for this color material amount conversion is created by measuring the color of a preprinted patch.

  Note that S403 to S409 are processing for the overlapping area 504 where two objects overlap each other. As described above, other areas where the objects do not overlap, ie, other areas where the objects do not overlap, can be converted into color material amount data as they are. Done. That is, in S410, since the region 503 is a non-transparent spectral image object in the data conversion unit 307, the LabPQR color space is directly converted into color material amount data. Since the area 505 is a transparent graphic object, it is transparently combined with the background and then converted to color material amount data.

  As described above, according to the present embodiment, in the region where the objects including the spectral images are overlapped, PQR is converted when converting from LabPQR, which is the first color space, to RGB color space, which is the second color space. Convert from Lab component only to RGB color space without using component. Therefore, when this conversion is performed by calculation, the conversion from LabPQR to RGB is usually a conversion from 6 dimensions to 3 dimensions, but in this embodiment, conversion from 3 dimensions to 3 dimensions is performed by not using PQR. Therefore, the calculation amount can be reduced. Also, when this conversion is performed using an LUT, a 6-dimensional to 3-dimensional LUT is usually required, but in this embodiment, a 3-dimensional to 3-dimensional LUT may be prepared. Alternatively, even when a 6-dimensional to 3-dimensional LUT is used, the range of possible values is reduced by using a fixed value or a rounded value as the PQR, so that the LUT size can be reduced.

<Modification>
In this embodiment, an example in which the transparent composition process is performed by the printer driver has been described, but the same process can be performed by the printer controller. In this case, the system configuration is the same as that in FIG. 1, but as the functional configuration, the driver UI input unit 202 and the driver UI output unit 203 in FIG. 2 become a controller UI input unit and a controller UI output unit, respectively. Further, the print data generation unit 205 that has generated the print data serves as a data reading unit that reads the print data that has already been generated. Also, the transparent composition processing in the printer controller is the same as the flowchart of FIG. 4 described above. However, the pop-up message displayed as a user notification in S405 is displayed on the printer control panel, and the page number being printed as shown in FIG. 10 is not notified, but there is a part where the spectral information is dropped during the transparent composition process. The fact is notified in the same manner.

  In this embodiment, an example is shown in which an object is divided and only an overlapping object is converted to the RGB color space. However, the entire object is converted to the RGB color space without dividing the object. Anyway.

  In this embodiment, an example in which print data is rasterized into color material amount data has been described. However, the present invention is not limited to such rasterization processing as long as the processing includes transmission image synthesis processing of spectral images. For example, the present invention may be applied to a system in which only a part of print data is rasterized and transparently combined and then converted to another print data.

  In this embodiment, the spectral image color space is all described as LabPQR. However, the present invention is applicable to any color space that includes a basic stimulus value component and a spectral additional information component. is there.

  The present invention can also be realized by executing the following processing. That is, software (program) that realizes the functions of the above-described embodiments is supplied to a system or apparatus via a network or various storage media, and a computer (or CPU, MPU, or the like) of the system or apparatus reads the program. It is a process to be executed.

Claims (11)

An image processing apparatus for transmitting and synthesizing another image with respect to an image of the subject expressed using spectral information indicating the spectral reflectance acquired at the time of photographing the subject,
For each of a plurality of images to be combined, a color for determining whether or not the color space expressing the image is a first color space composed of a basic component indicating a stimulus value and an additional component indicating spectral information Space determination means;
Of the plurality of images, an image determined by the color space determining means to be expressed in the first color space is used as a second image using only the value of the basic component in the first color space. First color space conversion means for converting into an image expressed in a color space;
A second color space that converts an image that is determined not to be expressed in the first color space by the color space determination unit among the plurality of images to an image that is expressed in the second color space. Conversion means;
Combining means for transmitting and synthesizing the plurality of images converted into the second color space by the first and second color space conversion means on the second color space;
An image processing apparatus comprising: An image processing apparatus for transmitting and synthesizing another image with respect to an image of the subject expressed using spectral information indicating the spectral reflectance acquired at the time of photographing the subject,
For each of a plurality of images to be combined, a color for determining whether or not the color space expressing the image is a first color space composed of a basic component indicating a stimulus value and an additional component indicating spectral information Space determination means;
Among the plurality of images, an image determined by the color space determination unit to be expressed in the first color space is reduced in the basic component value and data amount in the first color space. First color space conversion means for converting into an image expressed in a second color space using the value of the additional component converted as described above,
A second color space that converts an image that is determined not to be expressed in the first color space by the color space determination unit among the plurality of images to an image that is expressed in the second color space. Conversion means;
Combining means for transmitting and synthesizing the plurality of images converted into the second color space by the first and second color space conversion means on the second color space;
An image processing apparatus comprising:   The image processing apparatus according to claim 2, wherein the first color space conversion unit converts the value of the additional component into a predetermined fixed value.   The image processing apparatus according to claim 2, wherein the first color space conversion unit converts the value of the additional component into one of a plurality of predetermined reference values.   Further, the image processing apparatus further comprises color material amount conversion means for converting a composite image obtained as a result of the composition in the second color space by the composition means into color material amount data at the time of printing the composite image. The image processing apparatus according to claim 1. Furthermore, it has an extracting means for extracting an overlapping region where the plurality of images overlap each other from the plurality of images,
The first and second color space conversion means, the synthesis means, and the color material amount conversion means perform processing on the overlapping area in each of the plurality of images,
6. The color material amount conversion unit further converts a value in each color space from a value in each color space into the color material amount data for each of the regions other than the overlapping region in each of the plurality of images. Image processing apparatus.   The image processing apparatus according to claim 1, wherein each of the plurality of images is an object image indicating an individual object.   The image processing apparatus according to any one of claims 1 to 7, further comprising an informing unit that informs the user when the conversion by the first color space conversion unit has been performed. An image processing method for transmitting and synthesizing another image with respect to an image of the subject expressed using spectral information indicating the spectral reflectance acquired at the time of photographing the subject,
For each of a plurality of images to be combined, a color for determining whether or not the color space expressing the image is a first color space composed of a basic component indicating a stimulus value and an additional component indicating spectral information A space determination step;
Of the plurality of images, an image that is determined to be expressed in the first color space in the color space determination step is used as a second value using only the value of the basic component in the first color space. A first color space conversion step of converting to an image expressed in a color space;
Of the plurality of images, a second color space that converts an image that is determined not to be expressed in the first color space in the color space determination step into an image that is expressed in the second color space. A conversion step;
Combining the plurality of images converted into the second color space in the first and second color space conversion steps in the second color space,
An image processing method comprising: An image processing method for transmitting and synthesizing another image with respect to an image of the subject expressed using spectral information indicating the spectral reflectance acquired at the time of photographing the subject,
For each of a plurality of images to be combined, a color for determining whether or not the color space expressing the image is a first color space composed of a basic component indicating a stimulus value and an additional component indicating spectral information A space determination step;
Among the plurality of images, the image determined to be expressed in the first color space in the color space determination step is reduced in the basic component value and data amount in the first color space. A first color space conversion step of converting into an image expressed in a second color space using the value of the additional component converted as described above;
Of the plurality of images, a second color space that converts an image that is determined not to be expressed in the first color space in the color space determination step into an image that is expressed in the second color space. A conversion step;
Combining the plurality of images converted into the second color space in the first and second color space conversion steps in the second color space,
An image processing method comprising:   A program for causing a computer to function as each unit in the image processing apparatus according to any one of claims 1 to 8 when executed by the computer.

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