JP2023180036A - Image processing device and image processing method - Google Patents

Abstract

To provide a technique capable of generating a parameter for color processing without using a spectral radiance meter in a site.SOLUTION: A color conversion table which is generated on the basis of a photographed image of a color chart imaged by a first imaging apparatus in a first environment is acquired. First color data which is generated on the basis of color data acquired from the photographed image of the color chart imaged by the first imaging apparatus in a second environment different from the first environment and a color conversion table is acquired. Second color data which is generated on the basis of color data acquired from a photographed image of a color chart imaged by a second imaging apparatus in the second environment and conversion information is acquired. Conversion information in which an evaluation value based on the first color data and the second color data becomes smaller than a prescribed value is generated as a parameter for color processing.SELECTED DRAWING: Figure 1

Description

The present invention relates to color processing technology.

Conventionally, in order to achieve highly accurate color reproduction based on standards such as ACESRGB for digital cameras, color patches were measured using a spectral radiance meter, and colors were designed to match the standard values calculated from the measured values. This makes it possible to achieve highly accurate color reproduction. However, measurement using a spectral radiance meter has a problem in that it takes time to measure each color of the color chart one by one. In order to design each lighting unit with high precision at multiple locations, it is essential to shorten the measurement time.

In the technology disclosed in Patent Document 1, the illumination spectral characteristics of the environment in which an image is observed are acquired, the spectral radiance is estimated from the illumination spectral characteristics and the spectral reflectance data of the color chart, and the spectral radiance is estimated to be the signal value of the color chart. Profile data indicating the relationship with the tristimulus values determined from the spectral radiance is calculated. That is, it is possible to estimate the spectral radiance of a color patch only by measuring the spectral characteristics of illumination without measuring the spectral radiance of the color patch in the viewing environment.

Further, in Patent Document 2, a master chart image obtained by imaging a predetermined color chart with a master camera in a master studio and photographing parameters set in the master camera are sent to individual studios as master photographing parameters. Then, in the individual studio, the master photographing parameters are set as initial sub-photographing parameters in the camera to be corrected, and a predetermined color chart is photographed by the camera to be corrected to obtain a chart image. The master chart image and chart image thus obtained are compared, and the photographing parameters of the individual studios are changed according to the comparison result. Through the above processing, it is possible to realize color matching between the cameras in the master studio and the individual studios.

Japanese Patent Application Publication No. 2002-218266 Japanese Patent Application Publication No. 2002-195760

However, in the technique disclosed in Patent Document 1, the accuracy deteriorates when there is shading in the color chart or when the reflectance of white is not 100%. It is extremely difficult to remove shading in order to achieve highly accurate color reproduction, such as a color difference of 1.6 or less. In addition, with the technology disclosed in Patent Document 2, it is possible to match the color reproduction between two cameras in a short time, but the master studio and individual studios need to be in almost the same environment, and the master camera and individual studios must be in almost the same environment. Cameras in individual studios must also be of the same model. The present invention provides a technique that allows color processing parameters to be generated on-site without using a spectral radiance meter.

One aspect of the present invention includes a first acquisition unit that acquires a color conversion table generated based on a captured image of a color chart captured by a first imaging device in a first environment; a second acquisition means for acquiring first color data generated based on the color conversion table and color data acquired from a captured image of a color chart captured by the first imaging device in two environments; a third acquisition means for acquiring second color data generated based on conversion information and color data acquired from an image of the color chart taken by a second imaging device in a second environment; The present invention is characterized by comprising a generating means for generating, as a color processing parameter, the conversion information such that an evaluation value based on the first color data and the second color data is smaller than a predetermined value.

According to the present invention, it is possible to provide a technique capable of generating color processing parameters on-site without using a spectral radiance meter.

FIG. 1 is a block diagram showing an example of a system configuration. Flowchart showing the operation of the system. A diagram showing an example of a color chart. FIG. 3 is a block diagram showing a more detailed configuration example of the first subsystem. 5 is a flowchart showing the operation of the first subsystem. 5 is a flowchart showing details of processing in step S14. FIG. 3 is a block diagram showing a more detailed configuration example of the second subsystem. 5 is a flowchart showing the operation of the second subsystem. 5 is a flowchart showing details of the process in step S23. 5 is a flowchart showing the operation of the first subsystem. FIG. 3 is a block diagram showing a more detailed configuration example of the second subsystem. 5 is a flowchart showing details of the process in step S23. FIG. 2 is a block diagram showing an example of the hardware configuration of a computer device.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. Note that the following embodiments do not limit the claimed invention. Although a plurality of features are described in the embodiments, not all of these features are essential to the invention, and the plurality of features may be arbitrarily combined. Furthermore, in the accompanying drawings, the same or similar components are designated by the same reference numerals, and redundant description will be omitted.

[First embodiment]
First, an example of the configuration of a system according to this embodiment will be described using the block diagram of FIG. 1. As shown in FIG. 1, the system according to the present embodiment includes a subsystem (first subsystem) in master studio 1, which is a first environment, and a subsystem in studio 2, which is a second environment different from the first environment. (second subsystem).

The first subsystem includes a color chart 13, an imaging device 11, a spectral radiance meter 12, a calibration device 15, and an illumination device 14. On the other hand, the second subsystem includes a color chart 23, an imaging device 21, an imaging device 22, a generation device 25, and an illumination device 24. The calibration device 15 and the generation device 25 are configured to be capable of data communication with each other via a wired and/or wireless network.

The operation of the system according to this embodiment will be explained according to the flowchart of FIG. In step S1, the first subsystem generates calibration information. Details of step S1 will be described later. In step S2, the second subsystem generates a color conversion table using the calibration information. Details of step S2 will be described later.

A more detailed configuration example of the first subsystem will be described using the block diagram of FIG. 4. The lighting device 14 is a device provided in the master studio 1 to illuminate the master studio 1, and is configured to be able to provide illumination with various color temperatures. For example, the lighting device 14 may be a plurality of lighting devices that each provide illumination with a different color temperature (for example, various color temperatures from 3000K to 6500K). In that case, one of the plurality of lighting devices will operate (illuminate) according to user operation or control by the lighting device 14. Further, the lighting device 14 may be a single lighting device that sequentially switches to lighting with different color temperatures. By generating calibration information using colors acquired under illumination with various color temperatures, it is possible to increase the accuracy of calibration and improve robustness.

The color chart 13 is a sheet on which different colors are arranged. In this embodiment, in order to provide a concrete explanation, a sheet in which patches of multiple colors (20 colors in FIG. 3) are lined up is used as the color chart 13, as shown in FIG. 3, as an example. As the color chart 13, a commercially available color chart that can be used for color design is used.

The imaging device 11 images the color patch 13 in the first environment (under illumination by the lighting device 14), generates a captured image of the color patch 13 (an RGB image in which each pixel has an RGB value), and Output the captured image.

The spectral radiance meter 12 measures the color patch 13 in the first environment (under illumination by the lighting device 14) and outputs the measured value (XYZ value) of the color patch 13 (each patch). The calibration device 15 generates calibration information using the captured image output from the imaging device 11 and the measured value output from the spectral radiance meter 12.

Details of the above step S1, that is, the operation of the first subsystem will be explained according to the flowchart of FIG. 5. In step S11, the imaging device 11 images the color patch 13 in the first environment (under illumination by the lighting device 14), generates a captured image of the color patch 13, and outputs the generated captured image.

In step S12, the spectral radiance meter 12 measures the color patch 13 in the first environment (under illumination by the lighting device 14) and outputs the measured value of the color patch 13 (each patch). Then, when the imaging in step S11 and the measurement in step S12 are performed under illumination of various color temperatures (for example, each of 100 color temperatures sampled from the range of 3000K to 6500K) by the illumination device 14, The process proceeds to step S14 via step S13. On the other hand, if there remains a color temperature that has not yet been illuminated by the illumination device 14, the illumination device 14 illuminates the color temperature that has not yet been illuminated, and the process proceeds to step S11 via step S13.

In other words, when the process proceeds to step S14, captured images of the color patch 13 taken under various illuminations and measured values of the color patch 13 measured under various illuminations have been acquired.

In step S14, the calibration device 15 uses the captured images of the color patch 13 captured under various illuminations by the imaging device 11 and the measured values of the color patch 13 measured under various illuminations by the spectral radiance meter 12. Calibration information is generated using and. The details of the process in step S14 will be explained according to the flowchart in FIG.

In step S141, the input unit 151 acquires captured images of the color patch 13 captured by the imaging device 11 under various illuminations. In step S142, the input unit 151 obtains the measured values of the color chart 13 measured by the spectral radiance meter 12 under various illuminations.

In step S143, the generation unit 152 generates calibration information using the captured image obtained in step S141 and the measured value obtained in step S142. Below, details of the process for generating calibration information will be explained.

The generation unit 152 acquires the RGB values of each patch in the captured image acquired in step S141. Note that since each pixel value in an image area corresponding to one patch in a captured image may not be constant, the average of the RGB values within the image area may be taken as the RGB value of the one patch.

The generation unit 152 then optimizes color processing parameters (color processing parameters) using the RGB values of the patch in the captured image and the measured values (XYZ values) acquired in step S142. For example, the generation unit 152 calculates the following equation (1) using the RGB values of the patch in the captured image to obtain the XYZ values (Xi, Yi, Zi) of the patch.

Here, M is a color processing parameter and is a matrix with a size of 3x19. Ri, Gi, and Bi are the R value, G value, and B value of the patch, respectively. Then, the generation unit 152 calculates by substituting Xi, Yi, and Zi obtained by calculating the above equation (1) into each of X, Y, and Z of the following equations (2) to (6). , find the Lab values (Li, ai, bi) of the patch.

Here, Xn, Yn, and Zn are, for example, values calculated by multiplying the spectral radiance of a completely diffuse reflector with a reflectance of 100% by a color matching function. In addition, the generation unit 152 calculates the measurement values by substituting the measurement values X, Y, and Z obtained in step S142 into each of X, Y, and Z in the above equations (2) to (6). The Lab values (Lti, ati, bti) corresponding to the values are determined.

The generation unit 152 then obtains an evaluation value ΔE based on the difference between the Lab values (Li, ai, bi) and the Lab values (Lti, ati, bti) for each patch using the following equation (7).

In this way, the generation unit 152 calculates the evaluation value ΔE of each patch under various illuminations. Then, the generation unit 152 uses, for example, the attenuated least squares method to obtain a matrix (conversion information) M that is a color processing parameter that minimizes the sum of the evaluation values ΔE of each patch under various illuminations. At this time, the initial value of each element of matrix M is not limited to a specific value, for example, it may be a randomly set value, or it may be a recently calculated value of each element of matrix M3. good. Furthermore, the sum of ΔE does not necessarily have to be the minimum, and a matrix M that is smaller than a predetermined value may be obtained.

Then, the generation unit 152 calculates equation (1) using the RGB values and matrix M to obtain XYZ values corresponding to the RGB values. Then, for each of the plurality of RGB values, the generation unit 152 generates a registered color by associating the RGB value (color data before conversion) with the XYZ value (color data after conversion) obtained for the RGB value. A 3DLUT, which is a conversion table, is generated as calibration information. For the plurality of RGB values, for example, the RGB values shown in the following equation (8) are used.

The generation unit 152 then stores the calibration information generated in this way in the storage unit 153. In step S144, the output unit 154 outputs the calibration information stored in the holding unit 153 in step S143. In this embodiment, it is assumed that the output unit 154 outputs the calibration information to the generation device 25 of the second subsystem via the network. However, the output destination of the calibration information by the output unit 154 is not limited to the generation device 25. For example, the output unit 154 may output the calibration information to an external device that the generation device 25 can access. This allows the generation device 25 to acquire calibration information from the external device as needed.

In this way, various RGB colors are displayed based on the captured image of the color patch 13 captured by the imaging device 11 under the first environment and the measured values of the color patch 13 measured by the spectral radiance meter 12 under the first environment. Calibration information in which "XYZ values which are physical values independent of illumination" corresponding to the values are registered is generated. By using such calibration information, it is possible to perform calibration color bration that is less affected by the lighting in the studio 2.

Next, a more detailed configuration example of the second subsystem will be explained using the block diagram of FIG. 7. The lighting device 24 is a device provided in the studio 2 to illuminate the studio 2. The lighting device 24 may be the same lighting device as the lighting device 14 described above, or may be a lighting device different from the lighting device 14 described above.

The color chart 23 is a sheet on which different colors are arranged. In this embodiment, a sheet in which patches of a plurality of colors are lined up is used as the color chart 23 as an example to provide a specific explanation. The color chart 23 may be the same color chart as the color chart 13 described above, or may be a color chart different from the color chart 13 described above.

The imaging device 21 may be the imaging device 11 taken out from the master studio 1, or may be the same type of imaging device as the imaging device 11 described above. The imaging device 21 images the color patch 23 in the second environment (under illumination by the lighting device 24), generates a captured image of the color patch 23 (an RGB image in which each pixel has an RGB value), and Output the captured image.

The imaging device 22 is an imaging device that is a color design target, and may be the same imaging device as the imaging device 11 described above, or may be a different imaging device from the imaging device 11 described above. The imaging device 22 images the color patch 23 in the second environment (under illumination by the lighting device 24), generates a captured image of the color patch 23 (an RGB image in which each pixel has an RGB value), and Output the captured image.

The generation device 25 acquires the calibration information generated by the calibration device 15. Then, the generation device 25 uses the acquired calibration information, the captured image of the color patch 23 captured by the imaging device 21, and the captured image of the color patch 23 captured by the imaging device 22, A color conversion table for correcting (calibrating) the RGB values in the captured image captured by the device 22 is generated.

The details of the above step S2, that is, the operation of the second subsystem will be explained according to the flowchart of FIG. 8. In step S21, the imaging device 21 images the color patch 23 in the second environment (under illumination by the lighting device 24), generates a captured image of the color patch 23, and outputs the generated captured image.

In step S22, the imaging device 22 images the color patch 23 in the second environment (under illumination by the lighting device 24), generates a captured image of the color patch 23, and outputs the generated captured image.

In step S23, the generation device 25 acquires the calibration information generated by the calibration device 15. Then, the generation device 25 uses the calibration information, the captured image of the color patch 23 captured by the imaging device 21, and the captured image of the color patch 23 captured by the imaging device 22 to A color conversion table for correcting (calibrating) RGB values in a captured image is generated. The details of the process in step S23 will be explained according to the flowchart in FIG.

In step S231, the input unit 251 acquires the calibration information generated by the calibration device 15. In step S232, the input unit 251 obtains the captured image of the color patch 23 captured by the imaging device 21 and the captured image of the color patch 23 captured by the imaging device 22.

In step S233, the reflection unit 252 acquires the RGB values of each patch in the captured image of the color patch 23 captured by the imaging device 21. Note that since each pixel value in an image area corresponding to one patch in a captured image may not be constant, the average of the RGB values within the image area may be taken as the RGB value of the one patch. Then, the reflection unit 252 uses the RGB values of the patch in the captured image and the calibration information to obtain the XYZ values corresponding to the RGB values. More specifically, the reflection unit 252 acquires the XYZ values corresponding to the RGB values of the patch in the captured image from the calibration information. When acquiring (converting), a tetrahedral interpolation algorithm is used.

In step S234, the generation unit 253 acquires the RGB values of each patch in the captured image of the color chart 23 captured by the imaging device 22. Note that since each pixel value in an image area corresponding to one patch in a captured image may not be constant, the average of the RGB values within the image area may be taken as the RGB value of the one patch. The generation unit 253 then calculates the following equation (9) using the RGB values of the patch to obtain the XYZ values (Xj, Yj, Zj) of the patch.

Here, M2 is a color processing parameter and is a matrix having a size of 3x19. Rj, Gj, and Bj are the R value, G value, and B value of the patch, respectively. Then, the generation unit 253 calculates by substituting Xj, Yj, and Zj obtained by calculating the above equation (9) into each of X, Y, and Z of the above equations (2) to (6). , find the Lab values (Lj, aj, bj) of the patch.

Furthermore, the generation unit 253 converts the XYZ values obtained in step S233 into Lab values (Ltj, atj, btj) using the above equations (2) to (6). The generation unit 253 then calculates the evaluation value ΔE for each patch using the following equation (10).

In this way, the generation unit 253 calculates the evaluation value ΔE of each patch. Then, the generation unit 253 uses, for example, the attenuated least squares method to obtain a matrix M2 that is a color processing parameter that minimizes the sum of the evaluation values ΔE of each patch. At this time, the initial value of each element of matrix M2 is not limited to a specific value, for example, it may be a randomly set value, or it may be a recently calculated value of each element of matrix M2. good.

Then, the generation unit 253 calculates the above equation (9) for the plurality of RGB values using the RGB values and matrix M2 to obtain the XYZ values corresponding to the RGB values, and uses the XYZ values to calculate the following: Equation (12) is calculated to obtain the ACESRGB value corresponding to the XYZ value. Then, the generation unit 253 generates, for each of the plurality of RGB values, a 3DLUT that is a color conversion table in which the RGB value and the ACESRGB value obtained for the RGB value are registered in association with each other. For the plurality of RGB values, for example, the RGB values shown in the following equation (11) are used.

The generation unit 253 then stores the 3DLUT generated in this manner in the holding unit 254. By correcting the captured image captured by the imaging device 22 using the 3DLUT generated by the generation device 25, the color reproduction of the captured image captured by the imaging device 22 conforms to the ACESRGB standard. I can do it.

In step S235, the output unit 255 outputs the 3DLUT stored in the holding unit 254 in step S234. Note that the output destination of the 3DLUT by the output unit 255 is not limited to a specific output destination. For example, the output unit 255 may output the 3DLUT to the imaging device 22 or a device that corrects a captured image acquired from the imaging device 22. Further, the output unit 255 may generate a corrected captured image by correcting (color conversion) the captured image by the imaging device 22 using a 3DLUT, and output the corrected captured image. Note that the output destination of the corrected captured image by the output unit 255 is not limited to a specific output destination. For example, the output unit 255 may output the corrected captured image to a display device and display the corrected captured image on the display device, or output the corrected captured image to an external device via a wired and/or wireless network. You may also send it to. Further, the output unit 255 may generate print data based on the corrected captured image and output the print data to the printing device.

<Modification 1>
In the first embodiment, between devices (between the imaging device 11 and the calibration device 15, between the spectral radiance meter 12 and the calibration device 15, between the imaging device 21 and the generation device 25, between the imaging device 22 and the The data exchange with the generation device 25 has been described as being performed via a wired and/or wireless network. However, the method of exchanging data between devices is not limited to a specific method, and for example, data may be exchanged between devices via a memory device such as a UBS memory.

<Modification 2>
In the first embodiment, the calibration device 15 and the generation device 25 have been described as separate devices from the imaging device, but the calibration device 15 and the generation device 25 may be integrated with the imaging device.

For example, the calibration device 15 may be incorporated into the imaging device 11 in the form of hardware or software (firmware). Furthermore, for example, the generation device 25 may be incorporated into the imaging device 22 in the form of hardware or software (firmware).

<Modification 3>
In the first embodiment, XYZ values were converted to ACESRGB values according to equation (12), and a 3DLUT for converting RGB values to ACESRGB values was generated. However, the following equations (13) and (14) may be used instead of equation (12) to convert the XYZ values to sRGB values and generate a 3DLUT for converting the RGB values to sRGB values.

<Modification 4>
In the first embodiment, the evaluation value is not limited to ΔE obtained using the above equation (10), but may be, for example, ΔE′ obtained using the following equation (15).

<Modification 5>
In the first embodiment, processing using color data such as RGB values, XYZ values, Lab values, etc. was explained, but the color data used is not limited to color data in such color spaces, but also color data in other color spaces. Color data may also be used.

<Effects of the first embodiment>
The master imaging device is calibrated in advance using a spectroradiometer under a certain environment, and an imaging device of the same model as the calibrated master imaging device is used to image the same color chart as the imaging device to be color matched. By matching the colors between the image pickup device and the image pickup device to be color matched, it is possible to match the color reproduction of the image pickup device to be color matched with standards such as ACESRGB with high precision without using a spectral radiance meter on site. It is possible.

[Second embodiment]
In this embodiment, differences from the first embodiment will be explained, and unless otherwise mentioned below, it is assumed that the embodiment is the same as the first embodiment. In the first embodiment, in step S1, calibration information is generated for only one type of exposure condition without changing the exposure condition of the imaging device 11. However, depending on the brightness of the lighting in the studio 2, there is a possibility that the exposure at the time of calibration will not be appropriate. Therefore, in this embodiment, calibration information is generated for each different exposure condition, and calibration information corresponding to the brightness of the lighting in the studio 2 is selected and used.

The details of the above step S1, that is, the operation of the first subsystem will be explained according to the flowchart of FIG. 10. In step S15, the first subsystem (eg, calibration device 15) determines a reference exposure. For example, the standard exposure is such that the photographed value of gray with a reflectance of 18% in the color chart 13 becomes an intermediate value (32768 in the case of 16 bits). Then, the exposure is changed by 1/3 step in a range of ±2 steps from the standard exposure and photographed. Then, the first subsystem (for example, the calibration device 15) sets the exposure condition of the imaging device 11 to the reference exposure.

In step S11, the imaging device 11 images the color patch 13 in the first environment (under illumination by the lighting device 14) according to the set exposure conditions, generates a captured image of the color patch 13, and generates a captured image of the color patch 13. Output the captured image.

If the imaging device 11 captures images under all exposure conditions within the range of ±2 steps from the standard exposure, the process proceeds to step S12 via step S16. On the other hand, if there remain exposure conditions for which the imaging device 11 has not yet captured an image within a range of ±2 steps from the standard exposure, one of the remaining exposure conditions is set as the exposure condition of the imaging device 11. The process then proceeds to step S11 via step S16. When the process proceeds to step S12, captured images of the color patch 13 captured under various exposure conditions have been acquired.

In step S12, as in the first embodiment, the spectral radiance meter 12 measures the color patch 13 in the first environment (under illumination by the lighting device 14), and measures the measured value of the color patch 13 (each patch). Output.

Then, when the imaging in step S11 and the measurement in step S12 are performed under illumination of various color temperatures (for example, each of 100 color temperatures sampled from the range of 3000K to 6500K) by the illumination device 14, The process proceeds to step S14 via step S13. On the other hand, if there remains a color temperature that has not yet been illuminated by the illumination device 14, the illumination device 14 illuminates the color temperature that has not yet been illuminated, and the process proceeds to step S11 via step S13.

In other words, when the process proceeds to step S14, captured images of the color patch 13 taken under various illuminations and under various exposure conditions, and measured values of the color patch 13 measured under various illuminations have been acquired. It is.

In step S14, for each exposure condition, the calibration device 15 uses the captured images of the color patch 13 captured under various illumination conditions by the imaging device 11, and the images measured under various illuminations by the spectral radiance meter 12. Calibration information corresponding to the exposure conditions is generated using the measured values of the color patch 13 that have been obtained. The method for generating calibration information for one exposure condition is as explained in the first embodiment, so by performing the same process for each exposure condition, calibration information corresponding to each different exposure condition can be generated. can be generated.

Next, a more detailed configuration example of the second subsystem according to this embodiment will be described using the block diagram of FIG. 11. In FIG. 11, functional parts similar to those shown in FIG. 7 are given the same reference numerals, and a description of the functional parts will be omitted. The configuration shown in FIG. 11 has a selection section 256 added to the configuration shown in FIG. The selection unit 256 detects the brightness of the illumination 24 and controls the exposure conditions of the imaging device 21 according to the detected brightness.

The details of the process in step S23 according to this embodiment will be explained according to the flowchart of FIG. 12. In FIG. 12, the same step numbers as those in FIG. 9 are given the same step numbers, and explanations regarding the processing steps will be omitted.

In step S236, the input unit 251 acquires calibration information for each exposure condition generated by the calibration device 15. In step S237, the selection unit 256 selects the calibration information of the current imaging device 21 if there is calibration information with the same exposure condition as the current imaging device 21 among the calibration information for each exposure condition acquired in step S236. Select calibration information with the same exposure conditions as the exposure conditions. In this case, the selection unit 256 sets the variable EB to 0. On the other hand, if the selection unit 256 cannot find the calibration information with the same exposure condition as the current exposure condition of the imaging device 21, the selection unit 256 selects the calibration information closest to the current exposure condition of the imaging device 21 (the current exposure condition of the imaging device 21). Select the calibration information for the exposure condition (with the smallest number of steps of exposure difference). In this case, the selection unit 256 sets the number of steps of the exposure difference between the exposure condition corresponding to the selected calibration information and the current exposure condition of the imaging device 21 to the variable EB.

In step S238, the reflection unit 252 uses the calibration information selected in step S237 to obtain the XYZ values of each patch in the color chart 23 in the same manner as in the first embodiment (step S233). Then, the reflection unit 252 corrects the obtained XYZ values using the above-mentioned variable EB according to the following equation (16). The corrected XYZ values (X', Y', Z') are used in place of the XYZ values obtained in step S233 to perform subsequent processing.

<Effects of the second embodiment>
In addition to the effects of the first embodiment, even if the brightness of the lighting in the master studio 1 and the brightness of the lighting in the studio 2 are different, high precision can be achieved by selecting calibration information according to the brightness of the studio 2. It is possible to perform matching.

[Third embodiment]
The functional units of the calibration device 15 shown in FIG. 4 (excluding the holding unit 153) and the functional units of the generating device 25 shown in FIGS. 7 and 11 (excluding the holding unit 254) are implemented by software (computer program). It may also be implemented using hardware. In the former case, a computer device capable of executing the computer program can be applied to the calibration device 15 and the generation device 25. An example of a hardware configuration of a computer device applicable to the calibration device 15 and the generation device 25 will be described using the block diagram of FIG. 13. Note that the computer device applied to the calibration device 15 and the computer device applied to the generation device 25 may not have the same configuration.

The CPU 1301 executes various processes using computer programs and data stored in the RAM 1302 and ROM 1303. Thereby, the CPU 1301 controls the operation of the entire computer device, and also executes or controls the various processes described as being performed by the calibration device 15 and the generation device 25.

The RAM 1302 has an area for storing computer programs and data loaded from the ROM 1303 and the external storage device 1306, and an area for storing data received from the outside via the I/F 1307. Further, the RAM 1302 has a work area used when the CPU 1301 executes various processes. In this way, the RAM 1302 can provide various areas as appropriate.

The ROM 1303 stores configuration data for the computer device, computer programs and data related to starting the computer device, computer programs and data related to the basic operations of the computer device, and the like.

The operation unit 1304 is a user interface such as a keyboard, mouse, touch panel screen, etc., and can be operated by the user to input various instructions to the CPU 1301.

The display unit 1305 has a liquid crystal screen or a touch panel screen, and can display processing results by the CPU 1301 in the form of images, characters, and the like. Note that the display unit 1305 may be a projection device such as a projector that projects images and characters.

External storage device 1306 is a mass information storage device such as a hard disk drive. The external storage device 1306 stores computer programs and data for causing the CPU 1301 to execute or control the various processes described as being performed by the OS, the calibration device 15 and the generation device 25, and the like. Computer programs and data stored in the external storage device 1306 are loaded into the RAM 1302 as appropriate under the control of the CPU 1301, and are processed by the CPU 1301. The holding unit 153 in FIG. 4 and the holding unit 254 in FIGS. 7 and 11 can be implemented using a RAM 1302, a ROM 1303, an external storage device 1306, or the like.

The I/F 1307 includes an interface for connecting the imaging device 11, the spectral radiance meter 12, the imaging device 21, and the imaging device 22. The computer device can perform data communication with the imaging device 11, the spectral radiance meter 12, the imaging device 21, and the imaging device 22 via the I/F 1307.

The CPU 1301, RAM 1302, ROM 1303, operation unit 1304, display unit 1305, external storage device 1306, and I/F 1307 are all connected to a system bus 1308. Note that the hardware configuration shown in FIG. 13 is an example of the hardware configuration of a computer device that can be applied to the calibration device 15 and the generation device 25, and can be changed/modified as appropriate.

In addition, the numerical values, processing timing, processing order, processing subject, data (information) acquisition method/destination/source/storage location, color space, etc. used in each of the above embodiments and modifications are not specific. This is given as an example for the purpose of explanation, and is not intended to be limited to this one example.

Furthermore, some or all of the embodiments and modifications described above may be used in combination as appropriate. Furthermore, some or all of the embodiments and modifications described above may be selectively used.

(Other embodiments)
The present invention provides a system or device with a program that implements one or more functions of the embodiments described above via a network or a storage medium, and one or more processors in a computer of the system or device reads and executes the program. This can also be achieved by processing. It can also be realized by a circuit (for example, ASIC) that realizes one or more functions.

The invention in this specification includes the following image processing apparatus, image processing method, and computer program.

(Item 1)
a first acquisition unit that acquires a color conversion table generated based on a captured image of a color chart captured by a first imaging device in a first environment;
obtaining first color data generated based on the color conversion table and color data obtained from a captured image of a color chart captured by the first imaging device in a second environment different from the first environment; a second acquisition means for
a third acquisition unit that acquires second color data generated based on conversion information and color data acquired from an image of the color chart captured by a second imaging device in the second environment;
An image processing apparatus comprising: generating means for generating, as a parameter for color processing, the conversion information such that an evaluation value based on the first color data and the second color data is smaller than a predetermined value.

(Item 2)
The image processing apparatus according to item 1, wherein the first acquisition means acquires a color conversion table generated by an external device in the first environment.

(Item 3)
The first environment is an environment under illumination with different color temperatures,
The color conversion table includes color data generated based on conversion information and color data acquired from a captured image of a color chart captured by the first imaging device in the first environment, and color data generated based on conversion information; color data obtained based on the result of measuring the color chart at , color data before conversion based on the conversion information such that the evaluation value based on is the minimum, and color data after conversion are registered in association with each other. The image processing device according to item 1 or 2, wherein the image processing device is a 3DLUT.

(Item 4)
The second acquisition means acquires the Lab values corresponding to the XYZ values obtained by converting the RGB values acquired from the captured image of the color chart captured by the first imaging device in the second environment based on the color conversion table. Obtained as the first color data,
The third acquisition means acquires the Lab values corresponding to the XYZ values obtained by converting the RGB values acquired from the captured image of the color chart captured by the second imaging device in the second environment based on the conversion information. Obtained as second color data,
Any of items 1 to 3, characterized in that the generating means generates, as the parameter, the conversion information that minimizes the evaluation value based on the difference between the first color data and the second color data. The image processing device according to item 1.

(Item 5)
moreover,
Any one of items 1 to 4, characterized by comprising a color conversion table generation means for generating a color conversion table in which color data and color data obtained by converting the color data based on the parameters are registered in association with each other. The image processing device according to item 1.

(Item 6)
The color conversion table generation means calculates an ACESRGB value corresponding to the XYZ value obtained by converting the RGB value based on the parameter, and generates a color conversion table in which the RGB value and the ACESRGB value are registered in association with each other. The image processing device according to feature item 5.

(Item 7)
The color conversion table generation means calculates sRGB values corresponding to XYZ values obtained by converting RGB values based on the parameters, and generates a color conversion table in which the RGB values and the sRGB values are registered in association with each other. The image processing device according to feature item 5.

(Item 8)
moreover,
8. The image processing apparatus according to any one of items 1 to 7, further comprising an output means for outputting the color conversion table or a captured image that has undergone color conversion using the color conversion table.

(Item 9)
The first acquisition means acquires a color conversion table for each exposure condition,
The second acquisition means selects a color conversion table with an exposure condition closest to the exposure condition of the first imaging device from among the color conversion tables acquired by the first acquisition means, and selects a color conversion table with an exposure condition closest to the exposure condition of the first imaging device, and Items 1 to 8, characterized in that the first color data generated based on the selected color conversion table and the color data obtained from the captured image of the color chart captured by the imaging device are obtained. The image processing device according to any one item.

(Item 10)
The second acquisition means converts the RGB values acquired from the captured image of the color chart captured by the first imaging device in the second environment using the selected color conversion table, and calculates the XYZ values. The XYZ values are corrected according to the number of steps of exposure difference between the exposure conditions of the first imaging device and the exposure conditions of the selected calibration information, and the Lab values corresponding to the corrected XYZ values are corrected for the first color. The image processing device according to item 9, characterized in that the image processing device is acquired as data.

(Item 11)
An image processing method performed by an image processing device, the method comprising:
a first acquisition step in which a first acquisition unit of the image processing device acquires a color conversion table generated based on a captured image of a color chart captured by a first imaging device in a first environment;
A second acquisition unit of the image processing device includes color data acquired from a captured image of a color chart captured by the first imaging device in a second environment different from the first environment, and the color conversion table. a second acquisition step of acquiring first color data generated based on the
A second color generated by a third acquisition means of the image processing device based on conversion information and color data acquired from an image of the color chart captured by a second imaging device in the second environment. a third acquisition step of acquiring data;
a generation step in which the generation means of the image processing device generates, as a parameter for color processing, the conversion information such that an evaluation value based on the first color data and the second color data is smaller than a predetermined value. An image processing method characterized by:

(Item 12)
A computer program for causing a computer to function as each means of the image processing apparatus according to any one of items 1 to 10.

The invention is not limited to the embodiments described above, and various changes and modifications can be made without departing from the spirit and scope of the invention. Therefore, the following claims are hereby appended to disclose the scope of the invention.

1: Master studio 2: Studio 11: Imaging device 12: Spectral radiance meter 13: Color chart 14: Illumination device 15: Calibration device 21: Imaging device 22: Imaging device 23: Color chart 24: Illumination device 25: Generation device

Claims (12)

a first acquisition unit that acquires a color conversion table generated based on a captured image of a color chart captured by a first imaging device in a first environment;
obtaining first color data generated based on the color conversion table and color data obtained from a captured image of a color chart captured by the first imaging device in a second environment different from the first environment; a second acquisition means for
a third acquisition unit that acquires second color data generated based on conversion information and color data acquired from an image of the color chart captured by a second imaging device in the second environment;
An image processing apparatus comprising: generating means for generating, as a parameter for color processing, the conversion information such that an evaluation value based on the first color data and the second color data is smaller than a predetermined value. The image processing apparatus according to claim 1, wherein the first acquisition unit acquires a color conversion table generated by an external device in the first environment. The first environment is an environment under illumination with different color temperatures,
The color conversion table includes color data generated based on conversion information and color data acquired from a captured image of a color chart captured by the first imaging device in the first environment, and color data generated based on conversion information; color data obtained based on the result of measuring the color chart at , color data before conversion based on the conversion information such that the evaluation value based on is the minimum, and color data after conversion are registered in association with each other. The image processing apparatus according to claim 1, wherein the image processing apparatus is a 3DLUT. The second acquisition means acquires the Lab values corresponding to the XYZ values obtained by converting the RGB values acquired from the captured image of the color chart captured by the first imaging device in the second environment based on the color conversion table. Obtained as the first color data,
The third acquisition means acquires the Lab values corresponding to the XYZ values obtained by converting the RGB values acquired from the captured image of the color chart captured by the second imaging device in the second environment based on the conversion information. Obtained as second color data,
2. The generating means generates, as the parameter, the conversion information that minimizes the evaluation value based on the difference between the first color data and the second color data. Image processing device. moreover,
The image according to claim 1, further comprising color conversion table generation means for generating a color conversion table in which color data and color data obtained by converting the color data based on the parameters are registered in association with each other. Processing equipment. The color conversion table generation means calculates an ACESRGB value corresponding to the XYZ value obtained by converting the RGB value based on the parameter, and generates a color conversion table in which the RGB value and the ACESRGB value are registered in association with each other. The image processing device according to claim 5. The color conversion table generation means calculates sRGB values corresponding to XYZ values obtained by converting RGB values based on the parameters, and generates a color conversion table in which the RGB values and the sRGB values are registered in association with each other. The image processing device according to claim 5. moreover,
2. The image processing apparatus according to claim 1, further comprising an output means for outputting the color conversion table or a captured image subjected to color conversion using the color conversion table. The first acquisition means acquires a color conversion table for each exposure condition,
The second acquisition means selects a color conversion table with an exposure condition closest to the exposure condition of the first imaging device from among the color conversion tables acquired by the first acquisition means, and selects a color conversion table with an exposure condition closest to the exposure condition of the first imaging device, and 2. The first color data generated based on the selected color conversion table and the color data obtained from the captured image of the color chart captured by the imaging device. image processing device. The second acquisition means converts the RGB values acquired from the captured image of the color chart captured by the first imaging device in the second environment using the selected color conversion table, and calculates the XYZ values. The XYZ values are corrected according to the number of steps of exposure difference between the exposure conditions of the first imaging device and the exposure conditions of the selected calibration information, and the Lab values corresponding to the corrected XYZ values are corrected for the first color. The image processing apparatus according to claim 9, wherein the image processing apparatus is acquired as data. An image processing method performed by an image processing device, the method comprising:
a first acquisition step in which a first acquisition unit of the image processing device acquires a color conversion table generated based on a captured image of a color chart captured by a first imaging device in a first environment;
A second acquisition unit of the image processing device includes color data acquired from a captured image of a color chart captured by the first imaging device in a second environment different from the first environment, and the color conversion table. a second acquisition step of acquiring first color data generated based on the
A second color generated by a third acquisition means of the image processing device based on conversion information and color data acquired from a captured image of the color chart captured by a second imaging device in the second environment. a third acquisition step of acquiring data;
a generation step in which the generation means of the image processing device generates, as a parameter for color processing, the conversion information such that an evaluation value based on the first color data and the second color data is smaller than a predetermined value. An image processing method characterized by: A computer program for causing a computer to function as each means of the image processing apparatus according to claim 1.

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