Information processing device, information processing method, and program

Abstract

To enable a difference in color of images between imaging devices to be corrected regardless of recording modes of the imaging devices and the state of a subject.SOLUTION: An information processing device acquires imaging parameters of a first imaging device and a second imaging device, and determines the imaging number of first images captured by the first imaging device and the imaging number of second images captured by the second imaging device on the basis of the imaging parameters. The information processing device acquires first color information in the first image and second color information in the second image, and generates color correction information for correcting the difference in color between the first image and the second image on the basis of the first color information and the second color information.SELECTED DRAWING: Figure 3

Description

Technical Field

[0001] The present invention relates to a technique for generating information for color correction from a captured image.

Background Art

[0002] There is a system that performs imaging using a plurality of imaging devices (hereinafter referred to as cameras), and transmits a plurality of images obtained by those plurality of cameras after mixing or switching them. At this time, if the models, manufacturers, grades, etc. of the plurality of cameras used are different and there are significant differences in the imaging between those cameras, for example, when the camera is switched, the color may appear to change even though it is the same subject. Therefore, cameramen and video engineers (VEs) have to perform the work of adjusting each camera in advance so that the colors of the images are the same between each camera, which is a great burden. On the other hand, Patent Document 1 discloses a technique for imaging the same subject with each camera and correcting the color difference between the captured images. According to this technique, the burden of the work of adjusting each camera can be reduced.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Color differences in images between cameras can also occur depending on the recording mode of each camera and the condition of the subject in the field of view. For example, depending on the camera's recording mode and the condition of the subject in the field of view, the compression ratio when compressing the captured image by each camera may be high, in which case the color of the subject in the image may become different from its original color. In addition, in the technology of Patent Document 1, color correction data is created based on one frame of captured image. Therefore, if color correction data is created based on colors obtained from an image with a high compression ratio, the color correction data may perform correction on colors that should not be corrected.

[0005] Therefore, the present invention aims to correct the color differences in images between different imaging devices, regardless of the recording mode of the imaging device or the condition of the subject. [Means for solving the problem]

[0006] The information processing device of the present invention comprises a first imaging device and a second imaging device. This can affect the color of the image captured. The system is characterized by comprising: parameter acquisition means for acquiring imaging parameters; number determination means for determining the number of images to be captured by the first imaging device and the number of images to be captured by the second imaging device based on the imaging parameters; color information acquisition means for acquiring first color information contained in the determined number of first images and second color information contained in the determined number of second images; and generation means for generating color correction information that corrects the color difference between the first image and the second image based on the first color information and the second color information. [Effects of the Invention]

[0007] According to the present invention, it is possible to appropriately correct the color differences of images between different imaging devices, regardless of the recording mode of the imaging device or the condition of the subject. [Brief explanation of the drawing]

[0008] [Figure 1]This figure shows a schematic configuration example of the system according to the first embodiment. [Figure 2] This figure shows an example of the hardware configuration of an information processing device. [Figure 3] This figure shows an example of the functional configuration of the information processing device according to the first embodiment. [Figure 4] This is a flowchart showing the information processing flow according to the first embodiment. [Figure 5] This is a flowchart showing the flow of the color information acquisition process in the first embodiment. [Figure 6] This figure shows the relationship between imaging conditions and the number of images taken. [Figure 7] This is a diagram used to explain the image region from which color information is acquired. [Figure 8] This is a diagram showing the contents of color information. [Figure 9] This figure shows an example of the functional configuration of an information processing device according to the second embodiment. [Figure 10] This is a flowchart showing the color information acquisition process in the second embodiment. [Figure 11] This is a flowchart showing the information processing flow according to the third embodiment. [Figure 12] This is a flowchart showing the flow of the color information acquisition process in the third embodiment. [Figure 13] This figure shows a schematic configuration example of a system according to another embodiment. [Figure 14] This flowchart shows the information processing flow according to another embodiment. [Modes for carrying out the invention]

[0009] Embodiments of the present invention will be described below with reference to the drawings. The following embodiments are not limiting to the present invention, and not all combinations of features described in these embodiments are essential to the solutions of the present invention. The configuration of the embodiments may be modified or changed as appropriate depending on the specifications of the device to which the present invention is applied and various conditions (usage conditions, usage environment, etc.). Furthermore, parts of each embodiment described later may be combined as appropriate. In each of the following embodiments, the same components will be denoted by the same reference numerals.

[0010] [First Embodiment] In the first embodiment, a system in which an information processing device and multiple imaging devices are connected via a network will be described as an example. The information processing device in this embodiment determines the number of images to be captured based on the imaging parameters of each imaging device connected via the network, and acquires color information from the image data obtained from that number of images. Then, based on the color information acquired from the image data of that number of images, the information processing device in this embodiment generates a LUT (lookup table) of color correction information to correct the color differences between images captured by each imaging device. For the sake of simplicity in the following description, image data will be referred to simply as "image" as appropriate.

[0011] The system of this embodiment can be applied to systems that use multiple cameras to capture images, such as in live broadcasts of television programs or sports broadcasts, and then mix or switch between the images captured by these multiple cameras for broadcasting. In such a broadcasting system, for example, one camera can capture an image of the entire stadium, while other cameras capture images of players from various positions, making it possible to generate images that broadcast the match. Of course, the system of this embodiment is not limited to such broadcasting systems.

[0012] FIG. 1 is a diagram showing a schematic configuration example of a system 10 including an information processing apparatus 300 according to a first embodiment. In the system 10 shown in FIG. 1, the information processing apparatus 300 of the present embodiment and a plurality of imaging apparatuses such as a first imaging apparatus to a second imaging apparatus are connected via a network 400. In FIG. 1, a camera 100A is illustrated as the first imaging apparatus, and a camera 100B is illustrated as the second imaging apparatus, and only two cameras 100A and 100B are shown, but the number of cameras is not limited to two, and a larger number of cameras may be connected.

[0013] The network 400 connects a plurality of cameras 100A to 100B and the information processing apparatus 300 so that they can communicate with each other. The network 400 is composed of, for example, a plurality of routers, switches, cables, etc. that conform to the communication standard of Ethernet (registered trademark). Note that the communication standard, scale, and configuration of the network 400 are not limited as long as it can communicate between the cameras 100A to 100B and the information processing apparatus 300.

[0014] The information processing apparatus 300 has a controller function for controlling a plurality of cameras 100A to 100B and a function for generating a correction LUT for correcting colors between the cameras. The controller function is a function that enables setting of imaging parameters (hereinafter, may also be referred to as imaging conditions) for the cameras 100A to 100B, acquisition of the imaging parameters, control of the imaging operation of the cameras 100A to 100B, etc. Details of the imaging conditions of the cameras and their acquisition, etc. will be described later. The LUT generation function is a function that acquires color information (such as RGB values) from the image regions of the subjects in the images respectively captured by the cameras 100A to 100B, simultaneously generates importance information, and generates a LUT of color correction information based on these information. Details of the acquisition of color information and LUT generation will be described later. The LUT generated by the information processing apparatus 300 is output to the cameras via the network 400 and applied to the cameras. Thereby, it becomes possible to acquire images in which color differences between the cameras are corrected. The information processing apparatus 300 can be configured by a terminal device such as a personal computer (PC), a smartphone, or a tablet PC.

[0015] In this embodiment, as a subject, a color chart in which a plurality of color patches of different colors are arranged is taken as an example. Also in this embodiment, the importance information is a weighting coefficient for each color information. The weighting coefficient can be given not only as an integer but also as a decimal. For color information with high importance, when generating a LUT described later, weights are assigned so as to strongly reduce the color difference between a plurality of cameras as much as possible.

[0016] Cameras 100A to 100B each include a lens group and an imaging element that constitute an imaging optical system. The lens group has an optical lens or the like for forming an optical image of a subject or the like on the imaging element. The imaging element is an element that converts light into an analog image signal, and examples thereof include a CMOS element or the like. It is assumed that cameras 100A to 100B are cameras that capture one or more still images and moving images. [[ID=T8]]

[0017] In this embodiment, a camera that can image a target color to be matched between cameras is used as a reference camera, and another camera that is to be corrected to the same color as the image of the reference camera is referred to as a correction target camera. In this embodiment, for example, camera 100A in FIG. 1 is used as the reference camera, and camera 100B is used as the correction target camera for the following description.

[0018] FIG. 2 is a diagram showing an example of the hardware configuration of the information processing apparatus 300. The information processing apparatus 300 includes a CPU 201, a RAM 202, a ROM 203, an auxiliary storage I / F (interface) 204, an HDD 205, an input I / F 206, an output I / F 207, and a network I / F 212. Each component of the information processing apparatus 300 is interconnected by a system bus 208. The information processing apparatus 300 is connected to an external storage device 309 and an operation device 211 via the input I / F 206, and is connected to a display device 210 via the output I / F 207. It is assumed that the information processing apparatus 300 is connected to the network 400 shown in FIG. 1 via the network I / F 212.

[0019] The CPU 201 uses the RAM 202 as work memory, executes the control program stored in the ROM 203, and comprehensively controls each component of the information processing device 300 via the system bus 208. The CPU 201 also executes the information processing program stored in the ROM 203 to realize the information processing according to this embodiment, as described later. The HDD 205 is a storage device that stores various data, including image data handled by the information processing device 300. The CPU 201 writes data to the HDD 205 and reads data stored in the HDD 205 via the system bus 208. Note that the storage device is not limited to the HDD 205, and may include devices using various storage devices such as optical disc drives and flash memory.

[0020] The input interface 206 is a serial bus interface such as USB or IEEE1394. The information processing device 300 acquires data and commands from an external device via the input interface 206. The external storage device 309 has a storage medium such as a hard disk, memory card, CF card, SD card, or USB memory. The information processing device 300 acquires data from the external storage device 309 via the input interface 206. The operating device 211 is an input device that includes a mouse, keyboard, touch panel, etc., and receives instructions from the user. The information processing device 300 acquires the user's instructions input to the operating device 211 via the input interface 206.

[0021] The output I / F 207 is a serial bus I / F such as USB or IEEE1394, similar to the input I / F 206. The output I / F 207 may also be a video output terminal such as DVI or HDMI (registered trademark). The information processing device 300 outputs data to an external device via the output I / F 207. In this embodiment, the external device connected via the output I / F 207 is a display device 210 (various image display devices such as liquid crystal displays). The information processing device 300 outputs image data and various message information processed or generated by the CPU 201 to the display device 210 via the output I / F 207. In this embodiment, the data generated by the CPU 201 can include, for example, data showing the generation results of the LUT described later.

[0022] The network interface 212 includes connectors for connecting to a network such as Ethernet. The information processing device 300 can acquire image data captured by each camera via the network 400 connected through the network interface 212. The CPU 201 of the information processing device 300 stores this image data and information such as imaging conditions in the RAM 202 and HDD 205 via the system bus 208. Although the information processing device 300 has other components besides those shown in Figure 2, their illustrations and explanations are omitted here.

[0023] The information processing device 300 of this embodiment, having the configuration described above, acquires image data of the camera to be corrected 100B and image data of the reference camera 100A, which are input to the network I / F 212 via the network 400 under the control of the CPU 201. The information processing device 300 then acquires color information from the acquired image data and generates a LUT (Lookup Sheet) based on that color information to correct the color of the image of the camera to be corrected 100B to match the color of the image of the reference camera 100A.

[0024] [Functional Configuration of Information Processing Equipment] The functional configuration of the information processing device 300 according to this embodiment will be explained using the functional block diagram in Figure 3. Note that the configuration shown in Figure 3 can be modified or changed as appropriate. For example, one functional unit may be divided into multiple functional units according to their functions, or two or more functional units may be integrated into one functional unit. Furthermore, the configuration in Figure 3 may consist of two or more devices. In that case, each device is connected via a circuit or a wired or wireless network, and performs data communication with each other to cooperate in order to realize the processes described below as being performed by the information processing device.

[0025] In the following description, each functional unit shown in Figure 3 will be explained as the main processing unit; however, in practice, the functions of each functional unit will be realized by the CPU 201 executing the information processing program according to this embodiment. Note that each functional unit shown in Figure 3 may also be implemented as a hardware configuration.

[0026] The information processing device 300 is broadly divided into an input data processing unit 301 and a LUT generation unit 302. The input data processing unit 301 includes a condition acquisition unit 311, a condition storage unit 313, a number determination unit 314, an image acquisition unit 315, an image storage unit 317, a color information generation unit 318, and a relational information storage unit 322. The LUT generation unit 302 includes a correction information generation unit 319 and a format conversion unit 320.

[0027] The condition acquisition unit 311 acquires imaging conditions from the reference camera 100A and also from the camera to be corrected 100B. In this embodiment, the imaging conditions include at least one of the following: ISO sensitivity, shutter speed, aperture value, and image recording parameters. The image recording parameters include the image recording mode and image bitrate, in other words, the encoding method, bitrate, or encoding parameters (quantization parameters). In this embodiment, the condition acquisition unit 311 acquires imaging condition information set in the reference camera 100A and the camera to be corrected 100B, respectively, but it may also acquire imaging condition information entered by the user, for example.

[0028] The condition storage unit 313 stores the imaging conditions for each camera acquired by the condition acquisition unit 311. The imaging conditions stored in the condition storage unit 313 are referenced by the number of frames determination unit 314. The relationship information storage unit 322 stores correspondence information that describes the relationship between the number of images to be captured by the camera in order to obtain color information, and multiple different imaging conditions. Details of the correspondence information stored in the relationship information storage unit 322 that describes the relationship between the number of images to be captured and the imaging conditions for obtaining color information will be described later.

[0029] The image count determination unit 314 determines the number of images to be captured by each camera in order to obtain color information, based on the imaging conditions stored in the condition storage unit 313 and referring to the correspondence information stored in the relationship information storage unit 322. Specifically, the image count determination unit 314 determines the number of first images to be captured by the reference camera 100A and the number of second images to be captured by the correction target camera 100B, based on the imaging conditions of the reference camera 100A and the correction target camera 100B, and by referring to the correspondence information. Details of the image count determination process in the image count determination unit 314 will be described later. The information on the number of images to be captured determined by the image count determination unit 314 is sent to the image acquisition unit 315.

[0030] The image acquisition unit 315 sends imaging commands to each camera via the network 400 and acquires images captured by each camera in accordance with those commands. In other words, the image acquisition unit 315 instructs the reference camera 100A and the correction target camera 100B to take images for the number of images determined by the number of images determination unit 314, and acquires those number of images. The image storage unit 317 stores the number of images acquired by the image acquisition unit 315 from each camera.

[0031] The color information generation unit 318 acquires color information to be used for LUT generation from images acquired by the image acquisition unit 315 from the reference camera and the camera to be corrected and stored in the image storage unit 317. In this embodiment, first color information is acquired from the image area of ​​the subject in the first image taken by the reference camera 100A, and second color information is acquired from the image area of ​​the subject common to the first image in the second image taken by the camera to be corrected 100B. The color information generation unit 318 then outputs the acquired first and second color information as a pair to the correction information generation unit 319 of the LUT generation unit 302. The color information acquisition process in the color information generation unit 318 is assumed to be performed, for example, based on instructions from the user. Details of the color information acquisition process in the color information generation unit 318 will be described later.

[0032] The correction information generation unit 319 of the LUT generation unit 302 creates a LUT for correcting the color of the image acquired by the camera to be corrected, based on the set of color information generated by the color information generation unit 318. That is, the correction information generation unit 319 generates a color correction information LUT that corrects the color difference between the first image from the reference camera 100A and the second image from the camera to be corrected 100B, based on the set of first and second color information acquired by the color information generation unit 318. The method for creating the LUT can be, for example, the method disclosed in Reference 1. The method described in Reference 1 is known, so its explanation is omitted. Reference 1: Patent No. 3990971

[0033] The format conversion unit 320 converts the LUT generated by the correction information generation unit 319 into a format that the camera to be corrected can read (for example, a cube file), and outputs it as LUT data 321. When this LUT data 321 is applied to the camera to be corrected 100B, the image of the camera to be corrected 100B will match the color of the image of the reference camera 100A.

[0034] Next, the overall flow of information processing performed in the information processing device 300 of this embodiment will be explained using the flowchart in Figure 4. First, in step S401, the information processing device 300 sets imaging conditions for the reference camera 100A and the camera to be corrected 100B using the control function described above. The settings for imaging conditions for each camera include setting image recording parameters such as the image recording mode and image bitrate, as well as settings such as ISO sensitivity, shutter speed, and aperture value. In addition, the setting of the recording mode also includes the color gamut and gamma setting at the time of imaging. The settings for imaging conditions for the reference camera 100A and the camera to be corrected 100B may be set by user instruction via the information processing device 300, by the user directly setting each camera, or by settings performed automatically by each camera.

[0035] Next, in step S402, the input data processing unit 301 of the information processing device 300 acquires the imaging conditions set for the reference camera 100A and the camera to be corrected 100B in step S401, and determines the number of images to be captured to obtain color information based on those imaging conditions. Furthermore, the input data processing unit 301 causes the reference camera 100A to acquire the number of images determined based on those imaging conditions. Then, the input data processing unit 301 generates color information using the number of images acquired by the reference camera 100A. Details of the processing in step S402 will be described later.

[0036] In step S403, the input data processing unit 301 also causes the correction target camera 100B to acquire the number of images determined based on the imaging conditions. The input data processing unit 301 then generates color information using the number of images acquired by the correction target camera 100B. The processing in step S403 is the same as in step S402, except that the camera capturing the images changes from the reference camera to the correction target camera. Details of the processing in step S403 will be described later.

[0037] Next, in step S404, the correction information generation unit 319 of the LUT generation unit 302 acquires the sets of color information generated in steps S402 and S403, respectively, and performs color correction information generation processing using an optimization method. In this embodiment, the correction information generation unit 319 generates a LUT of color correction information to enable the correction target camera 100B to reproduce the color of the image from the reference camera 100A. As the optimization method, known methods such as the DLS method or the method described in the aforementioned reference 1 can be used.

[0038] DLS stands for Dumped Least Squares method. This method determines processing parameters so that the difference between a sequence of input data processed with certain processing parameters and the corresponding target data sequence approaches the target value sequence. Processing parameters can be, for example, a matrix, and an example of a target value is ΔE calculated from L*a*b* obtained based on RGB. A detailed explanation of the DLS method can be found in, for example, reference 2, but since this technique is publicly known, a detailed explanation will be omitted. Reference 2: "Lens Design," p. 194 (by Tomoaki Takahashi, Tokai University Press)

[0039] Next, in step S405, the format conversion unit 320 generates LUT data 321 by converting the LUT generated in step S404 into a format applicable to the camera 100B to be corrected. When this LUT data 321 is applied to the camera 100B to be corrected, the color of the image from the camera 100B to be corrected will generally match the color of the image from the reference camera 100A.

[0040] In the above description, the LUT is generated based on color information obtained from an image captured with a single exposure. However, this embodiment is not limited to this, and the LUT may be generated using color information obtained from images captured with multiple exposures. In this case, the process from step S401 to step S403 is repeated for each of the multiple exposures, i.e., for the number of imaging conditions.

[0041] [Details of the color information acquisition process] Next, the processing flow from determining the number of images to acquire color information based on the imaging conditions in steps S402 and S403 of Figure 4 will be explained using the flowchart in Figure 5. Note that in steps S402 and S403, the same processing is performed regardless of whether the camera capturing the image is the reference camera or the camera to be corrected, so here, we will not specify whether it is the reference camera or the camera to be corrected, and will simply refer to it as "camera".

[0042] In step S501, the condition acquisition unit 311 of the input data processing unit 301 acquires the camera imaging conditions set in step S401. The imaging condition information acquired by the condition acquisition unit 311 is then stored in the condition storage unit 313.

[0043] Next, in step S502, the number of images determination unit 314 determines the number of images Fn based on the imaging conditions stored in the condition storage unit 313 and the corresponding relationship information stored in the relationship information storage unit 322.

[0044] Figure 6(a) is a diagram showing an example of correspondence information stored in the relationship information storage unit 322. The correspondence information exemplified in Figure 6(a) shows the relationship between the image recording mode and the number of images captured. In other words, the correspondence information shown in Figure 6(a) represents the correspondence between the recording mode (encoding method) and bitrate information of the image recording parameters, which are an example of the camera's imaging conditions, and the number of images captured Fn. The number of images determination unit 314 determines the number of images captured Fn by referring to the correspondence information in Figure 6(a) based on the imaging conditions acquired in step S501. The reason for determining the number of images captured based on the imaging conditions of the encoding method and bitrate is that the compression ratio increases as the bitrate decreases, and as a result, the compressed image is more likely to be affected by block noise and other factors, and therefore more likely to have color errors compared to the original image. In the correspondence information exemplified in Figure 6(a), the number of images captured is determined to be larger as the bitrate decreases. By using the correspondence information in Figure 6(a) to determine the number of images, the number of images can be increased as the bitrate decreases, thus reducing the impact of color errors.

[0045] Furthermore, the correspondence information stored in the relationship information storage unit 322 may include information showing the relationship between the image recording mode and the number of images taken, for example, as shown in Figure 6(b). The correspondence information in Figure 6(b) represents the correspondence between the quantization parameter (encoding parameter) in H.264 and the number of images taken Fn, as an example of the image recording parameters for the camera's imaging conditions. The number of images determination unit 314 determines the number of images taken Fn for the imaging conditions acquired in step S501 by referring to the correspondence information shown in Figure 6(b). In other words, in the case of the quantization parameter, the larger its value, the more likely the quantized image is to be affected by noise and other factors, and the more likely it is that the color will have errors compared to the original image. For this reason, the correspondence information in Figure 6(b) is configured to determine a larger number of images taken as the value of the quantization parameter increases. By determining the number of images taken using this correspondence information in Figure 6(b), the number of images taken increases as the value of the quantization parameter increases, making it possible to reduce the influence of errors.

[0046] In addition, the number of images determination unit 314 may determine the number of images Fn based not only on the image recording parameters exemplified in Figures 6(a) and 6(b), but also on imaging conditions such as ISO sensitivity, shutter speed, and aperture value. That is, the color error of the captured image relative to the original color of the subject may be affected by noise generated due to ISO sensitivity, shutter speed, aperture value, etc. For example, when the ISO sensitivity is increased, the noise in the captured image tends to increase, when the shutter speed is fast, the noise tends to decrease, and when the aperture value is large, the noise tends to decrease. For this reason, the number of images determination unit 314 increases the number of images as the ISO sensitivity increases, as the shutter speed decreases, and as the aperture value decreases. This makes it possible to reduce the influence of noise caused by ISO sensitivity, shutter speed, aperture value, etc.

[0047] Let's return to the explanation in Figure 5. In step S503, the image acquisition unit 315 causes the camera to take one image of the subject and acquires that image. The image storage unit 317 then stores the image acquired by the image acquisition unit 315.

[0048] Next, in step S504, the color information generation unit 318 acquires color information from the image stored in the image storage unit 317 based on the user's specifications or the like. The details of the color information acquisition process performed by the color information generation unit 318 in step S504 based on user specifications, etc., will be explained with reference to Figure 7.

[0049] Figure 7(a) shows an example of a GUI window 701 displayed on the screen of the display device 210 in Figure 2, where the captured image is displayed. In this embodiment, a color chart is used as the subject, so a color chart image 702 of the color chart is displayed in the GUI window 701. Since the color chart consists of multiple color patches, each consisting of a different color, the color chart image 702 in the GUI window 701 displays the color patch images 703 of each color. Here, the user can select a desired color patch image 703, that is, a desired color, from the color chart image 702 by using the mouse or touch panel of the operating device 211. In the example of Figure 7(a), the area 704 shown by the dotted line is assumed to be the position selected and specified by the user within the color chart image 702. In other words, in this embodiment, the area 704 specified by the user is the position of the image area where the color information generation unit 318 acquires color information.

[0050] The color information generation unit 318 acquires the average pixel value of each pixel within the user-specified region 704 for each image captured, and obtains the average value over the number of images as color information. Furthermore, if multiple regions are specified from the color chart image 702 in the GUI window 701, the correspondence between multiple color information sources can be shown between cameras by assigning a number to each region selected by the user, as shown in Figure 7(b).

[0051] Let's return to the explanation in Figure 5. In step S505, the image acquisition unit 315 determines whether the number of images acquired from the camera has reached the number of images Fn determined in step S502, that is, whether the number of images taken by the camera is greater than or equal to Fn. If the number of images acquired from the camera has reached the number of images Fn, the image acquisition unit 315 proceeds to step S506. On the other hand, if the number of images acquired from the camera has not reached the number of images Fn, the image acquisition unit 315 increments the number of images to be acquired from the camera and then returns to step S503. As a result, the image acquisition unit 315 causes the camera to take one more image of the subject and acquires that image. Note that when acquiring color information from the second or subsequent images, it is preferable not to specify the acquisition position of the color information in step S505, but to acquire the color information using the acquisition position information specified for the previous images.

[0052] When the process proceeds to step S506, the color information generation unit 318 generates color information by averaging the average pixel value obtained in step S504 from the region of each image (Fn images) over the number of images (Fn). For example, if the number of images (Fn) is 4, the color information generation unit 318 generates color information by averaging the average pixel value obtained in step S504 from the user-specified image regions of the 4 images over the 4 images. The color information generation unit 318 then outputs the generated color information to the correction information generation unit 319 of the LUT generation unit 302.

[0053] As described above, the color information obtained from the specified image regions in the Fn images is data in which the image region and pixel value are associated for each camera. Here, in each of the Fn images, the color information of the image region of the same color patch at the same position on the color chart should ideally be the same value, and should be the same value even between multiple cameras. However, depending on the imaging conditions of the cameras, these colors may differ. Figures 8(a) to 8(c) show examples of color information for the same image region of the same color patch for each camera, for example, when the image regions of each color patch on the color chart are numbered sequentially from the top left to the right. Specifically, multiple cameras are designated as cameras A to C, and Figure 8(a) shows the same color chart image taken by camera A, Figure 8(b) by camera B, and Figure 8(c) by camera C, and each shows the color information obtained from the image region of the same color patch at the same position. However, in cameras A to C, due to differences in imaging conditions, the color information for the same color patch image region with the same number is different in each case.

[0054] The correction information generation unit 319 of the LUT generation unit 302 generates a LUT of color correction information that enables the correction of the image color of the camera to be corrected so that the color of the image area of ​​the color patch at the same position in the color chart image matches the color of the image area of ​​the same color patch captured by the reference camera. As described above, the information processing device of this embodiment generates a LUT that can correct the color differences in images between cameras, regardless of the imaging conditions such as the recording mode of each camera. This makes it possible to generate images in which the same subject has the same color across all cameras.

[0055] [Second Embodiment] Next, a second embodiment will be described. In the second embodiment, the process of acquiring color information from the reference camera in step S402 and the process of acquiring color information from the camera to be corrected in step S403 are different from the processes described in the first embodiment.

[0056] In the second embodiment, the information processing device 300 performs noise detection on the images captured by the reference camera 100A and the camera to be corrected 100B. In the second embodiment, it is determined whether the first color information obtained from the first image captured by the reference camera 100A and the second color information obtained from the second image captured by the camera to be corrected 100B contain color noise exceeding a predetermined color noise threshold. The information processing device 300 then determines whether to add more images based on the result of the color noise detection. In other words, in the second embodiment, the information processing device 300 adds more images if the first color information and the second color information contain color noise exceeding the color noise threshold.

[0057] In the second embodiment, the information processing device 300 calculates the amount of noise contained in the Fn images, which are determined in the same manner as in the first embodiment. In this embodiment, the amount of block noise is obtained as the amount of noise. Based on the amount of block noise obtained through the noise amount acquisition process, the information processing device 300 determines whether or not to use the Fn images as images from which to acquire the first and second color information, in other words, whether or not to use them when generating the LUT. If the amount of block noise obtained through the block noise amount acquisition process is greater than or equal to a predetermined block noise threshold, the information processing device 300 does not use the Fn images as images from which to acquire the first and second color information, and instead adds a predetermined number of images. The information processing device 300 then attempts to acquire color information using the images acquired through this addition. Furthermore, the information processing device in this embodiment allows setting a predetermined upper limit on the number of images, and performs a process to confirm the number of images to be taken so that the number of images does not exceed the upper limit.

[0058] The reason for determining the amount of block noise here is to counteract the possibility that block noise may be generated in the compressed image more than originally intended due to sudden intrusion of moving objects into the field of view or vibration of the subject or the camera itself during imaging of the subject (color chart). Thus, in the second embodiment, based on the block noise amount determination result, it is determined whether or not to acquire color information from the captured image, that is, whether or not LUT optimization is possible. If LUT optimization is difficult, an attempt is made to acquire color information using captured images obtained by adding more images. The information processing device 300 then acquires color information from the image and generates a LUT if the amount of block noise in the image obtained by the additional imaging is below a threshold. In this embodiment, a predetermined upper limit is set for the number of additional images, and the information processing device 300 acquires color information from the captured image and generates a LUT if the amount of block noise in the additional images within the upper limit is below a threshold. If the expected color information cannot be obtained from the additional images within the upper limit, the information processing device 300 displays a warning message, for example, and terminates the process.

[0059] Figure 9 is a diagram showing an example of the functional configuration of the input data processing unit 301 and the LUT generation unit 302 of the information processing device 300 according to the second embodiment. In the second embodiment, the configuration shown in Figure 9 can be modified or changed as appropriate. For example, one functional unit may be divided into multiple functional units according to their functions, or two or more functional units may be integrated into one functional unit. Furthermore, the configuration in Figure 9 may be composed of two or more devices, in which case each device is connected via a circuit or a wired or wireless network and performs cooperative operation by communicating data with each other. Figure 10 is a flowchart showing the flow of the color information acquisition process in steps S402 and S403 of Figure 4 in the input data processing unit 301 according to the second embodiment. Note that the description of the same configuration and processing as in the first embodiment described above will be omitted, and only the configuration and processing that differ from the first embodiment will be described here.

[0060] First, we will describe the functional components that differ from those of the first embodiment described above, in the functional configuration shown in Figure 9. The noise amount calculation unit 323 calculates the amount of noise contained in the image acquired by the image acquisition unit 315. In this embodiment, the noise amount calculated by the noise amount calculation unit 323 is the block noise amount. Details of the block noise amount calculation process will be described later.

[0061] The image quality determination unit 316 determines, based on the calculation result of the block noise amount by the noise amount calculation unit 323, whether the image acquired by the image acquisition unit 315 has image quality that can be used to acquire color information. In the second embodiment, the relational information storage unit 322 also stores the block noise threshold Th, and the block noise threshold Th read from the relational information storage unit 322 is input to the image quality determination unit 316 via the number of images determination unit 314. The image quality determination unit 316 then compares the block noise amount calculated by the noise amount calculation unit 323 with the block noise threshold Th read from the relational information storage unit 322. If the calculated block noise amount is greater than or equal to the block noise threshold Th, the image quality determination unit 316 determines that the image acquired by the image acquisition unit 315 does not have image quality that can be used to acquire color information. Details of these processes will be described later.

[0062] If the image quality determination unit 316 determines that the image does not have sufficient image quality to be used for acquiring color information, the image stored in the image storage unit 317 will not be used when generating color information in the color information generation unit 318. In this case, the number of images determination unit 314 will add more images to the number of images to be captured. As a result, the image acquisition unit 315 will have the camera acquire the additional images. At this time, the number of images determination unit 314 also performs a number confirmation process to ensure that the number of images captured does not exceed a predetermined upper limit due to the addition of images. Details of these processes will be described later.

[0063] The color noise calculation unit 324 performs a color noise acquisition process to calculate the amount of color noise included in the color information generated by the color information generation unit 318. The color noise determination unit 325 determines whether the amount of color noise calculated by the color noise calculation unit 324 exceeds the color noise threshold Thc. In the second embodiment, the relationship information storage unit 322 also stores the color noise threshold Thc, and the color noise determination unit 325 receives the color noise threshold Thc read from the relationship information storage unit 322 via the sheet count determination unit 314. The color noise determination unit 325 then compares the amount of color noise calculated by the color noise calculation unit 324 with the color noise threshold Thc read from the relationship information storage unit 322. That is, the color noise determination unit 325 determines whether the calculated amount of color noise exceeds the color noise threshold Thc. Details of these processes will be described later.

[0064] If the color noise determination unit 325 determines that the calculated amount of color noise exceeds the color noise threshold Thc, the image count determination unit 314 will add a predetermined number of images. This causes the image acquisition unit 315 to have the camera acquire the additional images. Details of these processes will be described later.

[0065] The message generation unit 330 outputs a message to the display device 210, for example, to warn the user if the number of images exceeds the upper limit during the image count confirmation process in the image count determination unit 314. The message information may be in any format, such as text information, icons, or other formats, and the same applies to the message information described below.

[0066] The information processing flow in the second embodiment will be explained below using the flowchart in Figure 10. In the second embodiment, after step S501, the process proceeds to step S1301 and then step S1302, before proceeding to step S503. After the process in step S503, the judgment process in step S1303 is performed, and based on the result of that judgment, either step S504 or step S1304 is performed. After the process in step S504 or step S1304, the judgment process in step S1305 is performed, and based on the result of that judgment, either step S505 or step S1306 is performed. After the process in step S506, the judgment process in step S1307 is performed, and based on the result of that judgment, the process in the flowchart ends or step S1308 is performed. After the process in step S1308, the process returns to step S503, and after the process in step S1306, the process in the flowchart ends.

[0067] After step S501, the process proceeds to step S1301. There, the image count determination unit 314 determines the number of images Fn based on the imaging conditions obtained in step S501 and the corresponding relationship information stored in the relationship information storage unit 322. Furthermore, in step S1301, the image count determination unit 314 obtains the upper limit number of images Lim for the image count confirmation process during additional imaging from the relationship information storage unit 322. The upper limit number of images Lim is a value set to prevent the number of re-imaging images from increasing indefinitely when re-imaging becomes necessary due to the effects of noise, etc. In this embodiment, it is set to, for example, 120.

[0068] Next, in step S1302, the number of images determination unit 314 reads out the block noise threshold Th and the color noise threshold Thc stored in the relational information storage unit 322. Specifically, the block noise threshold Th is the number of gradation steps found by block noise detection. The relational information storage unit 322 stores the block noise threshold Th which has been determined in advance. The color noise threshold Thc is the standard deviation of the average value of the color information for each image. For example, if the number of images is set to 8, the color information generation unit 318 will acquire the average value of the color information for each image area of ​​the 8 images. For this reason, the relational information storage unit 322 stores the standard deviation obtained from the color information obtained for each image area of ​​the 8 images of the color chart that have been captured in advance as the color noise threshold Thc. The number of images determination unit 314 sends the block noise threshold Th information read out from the relational information storage unit 322 to the image quality determination unit 316 and the color noise threshold Thc information to the color noise determination unit 325.

[0069] After step S503, the process proceeds to step S1303, where the noise amount calculation unit 323 calculates the amount of block noise for the image acquired in step S503. For calculating the amount of block noise, a method such as that disclosed in Reference 3 can be used. Since the method described in Reference 3 is known, its explanation is omitted. Reference 3: Japanese Patent Publication No. 2001-218210

[0070] Furthermore, in step S1303, the image quality determination unit 316 compares the block noise amount calculated by the noise amount calculation unit 323 with the block noise threshold Th and determines whether the block noise amount is greater than or equal to the block noise threshold (block noise ≥ Th). If the block noise amount is less than the block noise threshold Th, the image quality determination unit 316 determines that the image acquired in step S503 can be used as an image for generating color information. In this case, the image acquired in step S503 is used in the color information generation process by the color information generation unit 318. After that, the input data processing unit 301 proceeds to step S504. On the other hand, if the block noise amount is greater than or equal to the block noise threshold Th, the image quality determination unit 316 determines that the image acquired by the image acquisition unit 315 cannot be used as an image for generating color information. In this case, the image acquired in step S503 is not used in the color information generation process by the color information generation unit 318. After that, the input data processing unit 301 proceeds to step S1304.

[0071] When the process proceeds to step S1304, the image count determination unit 314 adds a predetermined number of images to the number of images to be captured, and the image acquisition unit 315 acquires that additional number of images. In this embodiment, the image count determination unit 314 adds 1 to the number of images to be captured (adds 1 image to the number of images to be captured), and the image acquisition unit 315 has the camera capture that additional 1 image to acquire it.

[0072] After step S504 or step S1304, if the process proceeds to step S1305, the image count determination unit 314 performs an image count confirmation process to determine whether the number of images captured is equal to or greater than the upper limit (image count ≥ Lim). For example, if the image count Fn is determined to be 8 in step S1301, and the number of images (frames) for which the block noise amount calculated in step S1303 is equal to or greater than the block noise threshold Th is 121, then the number of images captured is equal to or greater than the upper limit Lim. In this case, the image count determination unit 314 determines that the noise amount is larger than expected, and there is little prospect of capturing images that can be used to generate color information. In this case, the input data processing unit 301 proceeds to step S1306. On the other hand, if the image count determination unit 314 determines that the number of images captured is not equal to or greater than the upper limit Lim, the input data processing unit 301 proceeds to step S503. In this embodiment, the upper limit of the number of images (Lim) is set to 120, but this value is not limited to this value, and it may be changed depending on the imaging conditions, etc.

[0073] If the image count determination unit 314 determines that the number of images exceeds the upper limit and proceeds to step S1306, the message generation unit 330 generates a message indicating that, given the current situation, more images than expected will be needed to acquire color information, making color information acquisition difficult. The message information generated by the message generation unit 330 is then sent to the display device 210 and displayed. This allows the user to recognize that acquiring color information is difficult. After step S1306, the input data processing unit 301 completes the processing shown in the flowchart of Figure 10.

[0074] If the process proceeds to step S1307, the color noise calculation unit 324 calculates the amount of color noise included in the color information generated by the color information generation unit 318, and the color noise determination unit 325 determines whether the calculated amount of color noise is greater than the color noise threshold Thc. If the color noise determination unit 325 determines that it is greater than the color noise threshold Thc, the input data processing unit 301 proceeds to step S1308. On the other hand, if the color noise determination unit 325 determines that it is less than or equal to the color noise threshold (color noise ≤ Thc), the color information generated in step S506 is output to the LUT generation unit 302, and the input data processing unit 301 terminates the processing shown in the flowchart of Figure 10.

[0075] If the process proceeds to step S1308, the image count determination unit 314 adds a predetermined number of images to improve color noise. For example, if the number of images Fn was determined to be 8 in step S1301, the image count determination unit 314 adds 4 images as a further addition to the predetermined number of images. After that, the input data processing unit 301 proceeds to step S503.

[0076] As described above, according to the second embodiment, it is possible to correct the color differences between images from cameras regardless of the imaging conditions of each camera or the condition of the subject, and when acquiring color information, it is possible to acquire color information that can handle sudden noise fluctuations during imaging. Furthermore, according to the second embodiment, it is possible to check whether the generated color information is obtained as expected, so it is possible to generate a LUT for more accurate color correction of images between cameras.

[0077] [Third Embodiment] Next, a third embodiment will be described. In the third embodiment, the method for acquiring color information from the reference camera and the method for acquiring color information from the camera to be corrected in steps S402 and S403 differ from the method described in the previously described embodiment. Specifically, the information processing device 300 of the third embodiment performs a noise generation determination process based on the imaging conditions to determine whether a lot of noise is likely to occur. If, as a result of the noise generation determination process, the information processing device 300 determines that there is a high possibility of a lot of noise occurring, it displays a message to inform the user of this, and only generates a LUT for color correction if the user still wishes to continue processing. Note that the same configurations and processes as in the previously described embodiments will be omitted, and only the different configurations and processes will be described.

[0078] The functional configuration of the information processing device 300 according to the third embodiment is generally the same as that shown in Figure 3 above, but the input data processing unit 301 has a message generation unit 330. As will be described in detail later, in the third embodiment, the input data processing unit 301 performs a determination process based on the acquired imaging conditions to determine whether there is a high possibility that a lot of noise will be generated and it will be difficult to acquire color information. If it is determined that there is a high possibility that it will be difficult to acquire color information, the message generation unit 330 outputs message information to inform the user of this, and further outputs message information asking whether the user wants to change the settings of the imaging conditions. Details of these will be described later.

[0079] Figure 11 is a flowchart showing the overall processing flow in the information processing device 300 according to the third embodiment. In the flowchart of Figure 11, steps S404 and S405 are the same processes as steps S404 and S405 in the flowchart of Figure 4 described above, so their explanation is omitted.

[0080] First, in step S1001, the information processing device 300 sets imaging conditions for the reference camera 100A. The specific process for setting the imaging conditions is the same as the process described in step S401 above.

[0081] Next, in step S1002, the input data processing unit 301 acquires the imaging conditions of the reference camera 100A, determines the number of images to be captured to obtain color information based on those imaging conditions, and then acquires that number of images to generate color information. However, at this time, the input data processing unit 301 determines whether there is a high possibility that a lot of noise will be generated based on the imaging conditions, making it difficult to acquire color information, and generates and outputs message information according to the result of that determination. The details of the processing in step S1002 will be explained later using the flowchart in Figure 12.

[0082] Next, in step S1003, the input data processing unit 301 determines whether or not it was able to obtain color information in the process of step S1002. If it determines that it was able to obtain color information, the input data processing unit 301 proceeds to step S1005. On the other hand, if it determines that it was not able to obtain color information, the input data processing unit 301 proceeds to step S1004.

[0083] When the process proceeds to step S1004, the input data processing unit 301 determines whether the imaging settings of the reference camera 100A should be reviewed. For example, the input data processing unit 301 generates a message asking the user whether they want to review the settings and displays it on the display device 210, and makes a decision based on the user's input. If the user gives an instruction to review the settings, the input data processing unit 301 returns to step S1001; otherwise, it terminates the process shown in the flowchart in Figure 11.

[0084] If the process proceeds to step S1005, the information processing device 300 sets imaging conditions for the camera 100B to be corrected. The specific process for setting the imaging conditions is the same as the process described in step S401 above.

[0085] Next, in step S1006, the input data processing unit 301 acquires the imaging conditions of the camera 100B to be corrected, determines the number of images to be captured to obtain color information based on those imaging conditions, and then acquires that number of images to generate color information. However, at this time, the input data processing unit 301 determines whether there is a high possibility that a lot of noise will be generated based on the imaging conditions, making it difficult to acquire color information, and generates and outputs message information according to the result of that determination. The details of the processing in step S1006 will be explained later using the flowchart in Figure 12.

[0086] Next, in step S1007, the input data processing unit 301 determines whether or not color information was acquired in the process of step S1006. If it determines that color information was acquired, the information processing device 300 proceeds to step S404, which is performed by the LUT generation unit 302. On the other hand, if it determines that color information could not be acquired, the input data processing unit 301 proceeds to step S1008.

[0087] When the process proceeds to step S1008, the input data processing unit 301 determines whether the imaging settings of the camera 100B to be corrected should be reviewed. Here, as in step S1004, the input data processing unit 301 generates message information asking the user whether to review the settings and displays it on the display device 210, and makes a decision based on the user's input. If the user gives an instruction to review the settings, the input data processing unit 301 returns to step S1005, and if the user does not want to review the settings, it terminates the process shown in the flowchart in Figure 11.

[0088] Next, the flowchart in Figure 12 will be used to explain the details of the processing in steps S1002 and S1006 of Figure 11. Note that the camera used to capture the image for generating color information in steps S1002 and S1006 of Figure 11 is either the reference camera or the correction target camera. Since the same processing is performed regardless of whether it is the reference camera or the correction target camera, the cameras will not be specified here and will simply be referred to as cameras. Also, Figure 12 will only explain processing steps that differ from those in Figure 5 mentioned above. In the flowchart of Figure 12, after the processing in step S502, the processing from steps S901 to S903 is performed, and then the process proceeds to steps S503 and beyond.

[0089] After step S502, the process proceeds to step S901. The condition acquisition unit 311 determines, based on the imaging conditions acquired in step S501, whether there is a high probability of noise occurring in the image. Using the example in Figure 6(b) mentioned earlier, the condition acquisition unit 311 determines that there is a high probability of noise occurring if, for example, the quantization parameter of the imaging conditions is 40 or higher. If the condition acquisition unit 311 determines that there is a high probability of noise occurring, the input data processing unit 301 proceeds to step S902. On the other hand, if the condition acquisition unit 311 determines that there is no high probability of noise occurring, the input data processing unit 301 proceeds to step S503.

[0090] If the process proceeds to step S902, the message generation unit 330 generates message information indicating that there is a high probability of noise generation making it difficult to acquire color information, that is, message information indicating that noise is occurring and it is difficult to obtain valid data, and outputs this message to the display device 210. This allows the user to recognize that the current imaging conditions are such that noise is occurring and it is difficult to obtain valid data.

[0091] Furthermore, in step S902, the message generation unit 330 generates message information asking whether to continue processing under the current imaging conditions and outputs it to the display device 210. Next, in step S903, the message generation unit 330 determines whether or not the user has given an instruction to continue. If the user has given an instruction to continue, the input data processing unit 301 proceeds to step S503. On the other hand, if the user has given an instruction not to continue, the process shown in the flowchart of Figure 12 is terminated.

[0092] When the process proceeds to step 503 and beyond, image acquisition, color information addition, and other processes are performed in the same manner as described above. After that, the color information generated in step S506 is output to the LUT generation unit 302.

[0093] As described above, according to the third embodiment, a determination is made based on the camera's imaging conditions to determine whether noise is likely to occur, and if it is determined that processing should continue, the color information generation and LUT generation processes are performed.

[0094] [Other embodiments] Other embodiments will be described below. Figures 13(a) and 13(b) show schematic configuration examples of information processing systems in other embodiments. Figure 13(a) shows an example configuration of an information processing system comprising a dedicated information processing device 200A for receiving output images from camera 100A and a dedicated information processing device 200B for receiving output images from camera 100B. The controller 500 sets imaging conditions for each reference camera 100A and the camera to be corrected 100B. The information processing device 200A acquires the imaging conditions for the reference camera 100A, and the information processing device 200B acquires the imaging conditions for the camera to be corrected 100B. The information processing devices 200A and 200B may acquire the imaging conditions for each camera 100A and 100B from the controller 500 via the network 400, or they may acquire them from the respective connected cameras 100A and 100B. The information processing device 200A sets the number of images to be taken for the reference camera 100A and performs processing from the acquisition of the first image captured by the reference camera 100A to the generation of the first color information. The information processing device 200B sets the number of images to be captured for the camera 100B to be corrected, and performs processing from acquiring the second image captured by the camera 100B to generating the second color information. For example, the information processing device 200B generates a LUT using the first color information and the second color information and applies it to the camera 100B to be corrected. Alternatively, the information processing device 200A may generate the LUT, and the information processing device 200B may apply that LUT to the camera 100B. Alternatively, the controller 500, an external device connected to the information processing devices 200A and 200B, may generate the LUT.

[0095] Figure 13(b) shows an example of a system configuration where not all cameras 100A to 100B are connected to the network 400 simultaneously, but rather one camera at a time. In the system configuration shown in Figure 13(b), the overall processing flow in the information processing device 300 is as shown in the flowchart in Figure 14. In the flowchart of Figure 14, after the processing in step S402, the processing in step S1201 is performed, and then the process proceeds to steps S403 and beyond. In step S1201, the information processing device 300 switches the connection state between the network 400 and the camera to a state in which the reference camera 100A is first connected to the network 400. After the processing from acquiring the imaging conditions of the reference camera 100A to acquiring the first image and generating the first color information is performed, the information processing device 300 switches the connection to change the camera connected to the network 400 to the camera to be corrected 100B. After the processing from acquiring the imaging conditions of the camera to be corrected 100B to acquiring the second image and generating the second color information is performed, the information processing device 300 generates a LUT based on the first and second color information and applies it to the camera to be corrected 100B.

[0096] The present invention can also be realized by supplying a program that implements one or more of the functions of each of the embodiments described above to a system or device via a network or storage medium, and by having one or more processors in the computer of that system or device read and execute the program. It can also be realized by a circuit (e.g., an ASIC) that implements one or more functions. The embodiments described above are merely examples of how the present invention can be implemented, and the technical scope of the invention should not be interpreted as being limited by them. In other words, the present invention can be implemented in various ways without departing from its technical concept or its main features. [Explanation of Symbols]

[0097] 100A: Reference camera, 100B: Camera to be corrected, 300: Information processing device, 301: Input data processing unit, 302: LUT generation unit

Claims

1. A parameter acquisition means for acquiring imaging parameters that may affect the color of the image captured by the first imaging device and the second imaging device, A number determination means that determines the number of first images captured by the first imaging device and the number of second images captured by the second imaging device based on the aforementioned imaging parameters, A color information acquisition means for acquiring first color information contained in the first image of the determined number of images, and second color information contained in the second image of the determined number of images, A generation means that generates color correction information to correct the color difference between the first image and the second image based on the first color information and the second color information, An information processing device characterized by having the following features.

2. The information processing apparatus according to claim 1, characterized in that the color information acquisition means acquires the first color information and the second color information for an image region of a subject that is included in common to the first image and the second image.

3. The information processing apparatus according to claim 2, characterized in that the color information acquisition means acquires the average pixel value of each pixel in the image region for each of the number of images captured and generates the average value over the number of images as the color information.

4. It has a storage means for storing correspondence information that represents the relationship between multiple imaging parameters and the number of images taken, The information processing apparatus according to any one of claims 1 to 3, characterized in that the number of images determination means determines the number of images based on the imaging parameters and by referring to the stored correspondence relationship information.

5. The system includes a color noise acquisition means for acquiring the amount of color noise contained in the first color information and the second color information, The information processing apparatus according to any one of claims 1 to 4, characterized in that the number of images determination means adds a predetermined number of images if the amount of color noise exceeds a predetermined threshold.

6. Noise amount acquisition means for acquiring the amount of noise contained in the first image and the second image, Based on the amount of noise, the adoption determination means determines whether or not to adopt the first image and the second image as images from which the color information acquisition means will acquire the color information. The information processing apparatus according to any one of claims 1 to 5, characterized by having the following features.

7. The information processing apparatus according to claim 6, characterized in that the adoption determination means determines that if the amount of noise exceeds a predetermined threshold, the color information acquisition means will not adopt the first image and the second image as images for which it acquires color information.

8. The information processing apparatus according to claim 7, characterized in that the number of images determination means adds a predetermined number to the number of images if the adoption determination means determines that the color information acquisition means does not adopt the first image and the second image as images for which the color information is acquired.

9. The information processing apparatus according to claim 8, characterized in that the number of images determination means ensures that the number of images does not exceed the upper limit by adding the number of images.

10. The information processing apparatus according to any one of claims 6 to 9, characterized in that the noise amount acquisition means acquires the amount of block noise contained in the image.

11. The information processing device according to any one of claims 1 to 10, characterized in that the imaging parameters include ISO sensitivity, shutter speed, aperture value, and image recording parameters.

12. The information processing apparatus according to claim 11, characterized in that the image recording parameters include either an image encoding scheme or encoding parameters.

13. A means for determining whether noise is likely to occur in the image based on the aforementioned imaging parameters, If it is determined that noise is likely to occur in the image, the output means outputs message information prompting a change in the imaging parameters. An information processing apparatus according to any one of claims 1 to 12, characterized by having the following features.

14. The information processing apparatus according to any one of claims 1 to 13, characterized in that the generation means generates a lookup table of the color correction information.

15. The information processing apparatus according to any one of claims 1 to 14, characterized by having a switching connection means for switching between a state of being connected to the first imaging device and a state of being connected to the second imaging device.

16. A first information processing device having: parameter acquisition means for acquiring imaging parameters that may affect the color of an image captured by a first imaging device; number determination means for determining the number of first images to be captured by the first imaging device based on the imaging parameters; and color information acquisition means for acquiring first color information of the first images of the determined number of images. A second information processing device comprising: parameter acquisition means for acquiring imaging parameters that may affect the color of an image captured by a second imaging device; number determination means for determining the number of images to be captured by the second imaging device based on the imaging parameters; and color information acquisition means for acquiring the second color information of the determined number of images of the second image; Either the first information processing device or the second information processing device, or an external device connected to both the first and second information processing devices, generates color correction information that corrects the color difference between the first image and the second image based on the first color information and the second color information. An information processing system characterized by the following:

17. A parameter acquisition step for acquiring imaging parameters that may affect the color of the image captured by the first imaging device and the second imaging device, A number determination step, which determines the number of images to be captured by the first imaging device and the number of images to be captured by the second imaging device, based on the aforementioned imaging parameters. A color information acquisition step of acquiring first color information contained in the first image of the determined number of images and second color information contained in the second image of the determined number of images, A generation step that generates color correction information that corrects the color difference between the first image and the second image based on the first color information and the second color information, An information processing method characterized by having the following features.

18. A program for causing a computer to function as an information processing device according to any one of claims 1 to 15.

Images