Image processing device, image processing method, and image processing program

Abstract

Provided is an image processing device that executes a process for acquiring a first captured image obtained by imaging in a state in which a color developing member that develops color with a saturation distribution corresponding to an applied energy value overlaps a sheet-shaped member that has a first spectral transmittance, the sheet-shaped member having a second spectral transmittance, the sheet-shaped member having a second spectral transmittance, and the color developing member having a saturation distribution corresponding to the applied energy value. A pattern which is different from the first spectral transmittance and has a second spectral transmittance in the wavelength range of the color for calculating the saturation is formed; and extracting a pattern on the basis of the light attenuation distribution in the acquired first captured image.

Description

Technical Field

[0001] This invention relates to an image processing apparatus, an image processing method, and an image processing program. Background Technology

[0002] Previously, a technique was known to measure energy values ​​using a color-developing component that develops color based on the applied energy value. For example, one such color-developing component is Prescae (registered trademark) (manufactured by FUJIFILM Corporation), which develops color based on applied pressure.

[0003] Japanese Patent Application Publication No. 2015-215291 discloses a technique for correcting the tilt of an image of the inner region of a ring mark based on four reference points of an image obtained by taking a picture in a state where a ring mark with four reference points overlaps with a pressure-sensitive film. Summary of the Invention

[0004] The technical problem to be solved by the invention

[0005] It is preferable to extract the pattern with high precision from an image obtained by capturing an image in which a sheet-like component with a pattern forming a mark for image correction overlaps with a color-developing component to which energy is applied. However, in the technology described in Japanese Patent Application Publication No. 2015-215291, only the inner region of the ring mark is used as the correction target set on the ring mark and using four reference points, and therefore the overlap between the reference points and the color-developing part in the image is not considered.

[0006] The purpose of this invention is to provide an image processing apparatus, image processing method, and image processing program capable of extracting patterns with high precision from an image obtained by taking a picture in a state where the pattern overlaps with the colored portion of the color-developing component.

[0007] means for solving technical problems

[0008] The image processing apparatus of the first method is an image processing apparatus having at least one processor, which performs the following processing: acquiring a first photographic image obtained by taking a picture in a state where a color-developing component and a sheet-like component overlap, wherein the color-developing component develops color with a saturation distribution corresponding to an applied energy value, the sheet-like component has a first spectral transmittance, and forms a pattern that is different from the first spectral transmittance and has a second spectral transmittance at least in the wavelength range of the color used to calculate saturation; deriving a light attenuation distribution in the acquired first photographic image based on reference data corresponding to a light attenuation distribution that serves as a reference and the signal value of the acquired first photographic image; and extracting the pattern based on the derived light attenuation distribution.

[0009] In the image processing apparatus of the second method, the transmittance of the second spectrum is lower than that of the first spectrum in the image processing apparatus of the first method.

[0010] In the image processing apparatus of the third method, the second spectral transmittance is constant within the wavelength range of visible light in the image processing apparatus of the first or second method.

[0011] In the image processing apparatus of the fourth method, in any of the image processing apparatuses of the first to third methods, the processor uses the first photographic image to derive the distribution of energy values ​​applied to the color developing component.

[0012] In the image processing apparatus of any of the first to fourth embodiments, the processor performs image processing to correct the distortion of the first photographic image based on the extracted pattern.

[0013] In the image processing apparatus of any of the first to fifth embodiments, the processor performs the following processing: acquiring multiple first photographic images obtained by respectively photographing different partial regions of the overlapping color-developing component and the sheet-like component; and synthesizing first photographic images representing adjacent partial regions based on the extracted patterns.

[0014] In the image processing apparatus of any of the first to sixth embodiments, the processor performs the following processing: acquiring a plurality of first photographic images obtained by continuous shooting in a state where the color developing component and the sheet-like component overlap; and generating a shake-corrected first photographic image based on the pattern extracted for each of the plurality of first photographic images.

[0015] In the image processing apparatus of any of the first to seventh embodiments, the processor controls the capture of a first photographic image in a state where the color developing component and the sheet-like component overlap.

[0016] In the image processing apparatus of the ninth embodiment, in any one of the first to eighth embodiments, the reference data is the signal value of a second photographic image obtained by photographing a color developing component with a light attenuation distribution serving as a reference.

[0017] The image processing method of the 10th method is performed by a processor provided by an image processing device as follows: acquiring a first photographic image obtained by taking a picture in a state where a color-developing component and a sheet-like component overlap, wherein the color-developing component develops color with a saturation distribution corresponding to an applied energy value, the sheet-like component has a first spectral transmittance, and forms a pattern that is different from the first spectral transmittance and has a second spectral transmittance at least in the wavelength range of the color used to calculate saturation; deriving the light attenuation distribution in the acquired first photographic image based on reference data corresponding to a light attenuation distribution that serves as a reference and the signal value of the acquired first photographic image; and extracting the pattern based on the derived light attenuation distribution.

[0018] The image processing program of the 11th method is used to cause the processor of the image processing apparatus to perform the following processing: acquiring a first photographic image obtained by taking a picture in a state where a color-developing component and a sheet-like component overlap, the color-developing component developing colors with a saturation distribution corresponding to an applied energy value, the sheet-like component having a first spectral transmittance, and forming a pattern that is different from the first spectral transmittance and has a second spectral transmittance at least in the wavelength range of the color used to calculate saturation; deriving the light attenuation distribution in the acquired first photographic image based on reference data corresponding to a light attenuation distribution that serves as a reference and the signal value of the acquired first photographic image; and extracting the pattern based on the derived light attenuation distribution.

[0019] Invention Effects

[0020] According to the present invention, a pattern can be extracted with high precision from an image obtained by taking a picture in a state where the pattern overlaps with the colored portion of the color-developing component. Attached Figure Description

[0021] Figure 1 This is a block diagram illustrating an example of the general structure of a pressure measurement system.

[0022] Figure 2 This is a diagram showing an example of a color-developing component.

[0023] Figure 3 This is an example of a patterned sheet-like component.

[0024] Figure 4 It is a graph used to illustrate the spectral transmittance of the pattern.

[0025] Figure 5 This is a block diagram illustrating an example of the hardware structure of an image processing device.

[0026] Figure 6 This is a graph representing an example of feature data.

[0027] Figure 7This is a block diagram illustrating an example of the functional structure of an image processing device.

[0028] Figure 8 It is a diagram used to illustrate the scope of photography.

[0029] Figure 9 This is a flowchart illustrating an example of a pressure measurement process. Detailed Implementation

[0030] Hereinafter, examples of embodiments for carrying out the technology of the present invention will be described in detail with reference to the accompanying drawings. In this embodiment, an example in which pressure is applied as energy to the object will be described. Examples of objects to which pressure is applied include plate-shaped metal and semiconductor wafers.

[0031] First, refer to Figure 1 The structure of the pressure measuring system 1 according to this embodiment will be described. For example... Figure 1 As shown, the pressure measurement system 1 includes an image processing device 10. Examples of the image processing device 10 include portable computers such as smartphones or tablets. Alternatively, the image processing device 10 can also be a desktop computer.

[0032] like Figure 2 As shown, the pressure measuring system 1 uses a colorimetric component 90 that measures the energy value by displaying a saturation distribution corresponding to the applied energy value when energy (pressure in this embodiment) is applied. Figure 2 In the example, the portion filled with a diagonal line represents the colored portion. Specifically, the image processing device 10 uses a camera 40 (see reference). Figure 3 The image shows the color-developing component 90 in a state where color is developed by applying energy, and the energy value applied to the color-developing component 90 is derived from the image.

[0033] As the color developing component 90, for example, a Prescale (registered trademark) (manufactured by FUJIFILM Corporation) can be used to obtain a color development concentration corresponding to the applied pressure. Prescale is a substance containing a color developer with microcapsules containing a colorless dye, and the color developer is coated on a sheet-like support. When pressure is applied to the Prescale, the microcapsules are broken, and the colorless dye is adsorbed onto the color developer, resulting in color development. Furthermore, the color developer contains various microcapsules of different sizes and strengths; therefore, the color development concentration varies depending on the amount of microcapsules broken by the applied pressure. Thus, by observing the color development concentration, the magnitude and pressure distribution of the pressure applied to the Prescale can be determined. In addition, not only the color concentration but also the saturation changes with pressure.

[0034] Furthermore, in this embodiment, when the image processing apparatus 10 uses the camera 40 to photograph the color developing component 90, the sheet-like component 92 having a first spectral transmittance is superimposed on the color developing component 90. For example... Figure 3 As shown, a pattern P having a second spectral transmittance different from the first spectral transmittance is formed on the sheet-like component 92. Figure 3 The image shows an example of applying a grid pattern as pattern P. Furthermore, pattern P is not limited to a grid pattern; it can also be a pattern of shapes such as text or numbers, or a pattern of symbols such as triangles.

[0035] In this embodiment, the first spectral transmittance is, for example, 99%, a value infinitely close to 100%. That is, the sheet-like component 92 is a transparent sheet. Furthermore, the second spectral transmittance is lower than the first spectral transmittance and is constant, at least within the wavelength range of the color used to calculate saturation. Here, "constant" refers to a constant level of tolerance, including manufacturing errors. As an example, such as... Figure 4 As shown by the solid line, in this embodiment, the second spectral transmittance is constant at 80% across all wavelengths. Furthermore, the second spectral transmittance is preferably 50% or more and 80% or less. Figure 4 In the diagram, the dashed line represents the spectral transmittance of R (Red), the single-dotted-dashed line represents the spectral transmittance of G (Green), and the double-dotted-dashed line represents the spectral transmittance of B (Blue). Colors with constant spectral transmittance across all wavelengths are also called achromatic colors, appearing gray to the human eye. Secondary spectral transmittance is not limited to being constant across all wavelengths. For example, secondary spectral transmittance can be constant within the visible light wavelength range (e.g., from 360 nm to 830 nm). Furthermore, for example, when the colors used to calculate saturation are R, G, and B, secondary spectral transmittance can be constant within the wavelength range of R (e.g., from 640 nm to 770 nm), the wavelength range of G (e.g., from 490 nm to 550 nm), and the wavelength range of B (e.g., from 430 nm to 490 nm).

[0036] Next, refer to Figure 5 The hardware structure of the image processing apparatus 10 according to this embodiment will be described. For example... Figure 5As shown, the image processing apparatus 10 includes a CPU (Central Processing Unit) 20, a memory 21 serving as a temporary storage area, and a non-volatile storage unit 22. Furthermore, the image processing apparatus 10 includes a display 23 such as a liquid crystal display, an input device 24 such as a touch panel, a network I / F (Interface) 25 connected to a network, and a camera 40. The CPU 20, memory 21, storage unit 22, display 23, input device 24, network I / F 25, and camera 40 are connected to a bus 27. The CPU 20 is an example of a processor according to the technology of this invention.

[0037] The storage unit 22 is implemented using HDD (Hard Disk Drive), SSD (Solid State Drive), flash memory, etc. The storage unit 22, which serves as the storage medium, stores the image processing program 30. After the CPU 20 reads the image processing program 30 from the storage unit 22, it loads it into the memory 21 and executes the loaded image processing program 30.

[0038] Furthermore, the storage unit 22 stores feature data 32 and reference signal value data 34. Figure 6 An example of feature data 32 is shown. Feature data 32 is data that predetermines the relationship between the energy value (in this embodiment, the pressure value) applied to the color developing element 90 and the saturation of the color developing element 90 contained in an image obtained by photographing the color developing element 90. As the energy value, for example, a physical quantity corresponding to the energy that can be measured using the color developing element 90, such as the pressure value, can be appropriately applied. Furthermore, in Figure 6 In this context, pressure value is proportional to saturation, but the relationship between pressure value and saturation does not necessarily have to be limited to a proportional relationship.

[0039] Reference signal value data 34 is an example of reference data corresponding to the optical attenuation distribution that serves as a reference. Details regarding reference signal value data 34 will be described later.

[0040] The camera 40 is equipped with an image sensor such as a CCD (Charge Coupled Device) image sensor or a CMOS (Complementary Metal Oxide Semiconductor) image sensor. The camera 40 captures images of the color display component 90 and outputs the captured images to the CPU 20.

[0041] Next, refer to Figure 7 The functional structure of the image processing apparatus 10 according to this embodiment will be described. For example... Figure 7As shown, the image processing apparatus 10 includes a camera control unit 50, an acquisition unit 52, a first export unit 54, an extraction unit 56, an image processing unit 58, and a second export unit 60. The image processing program 30 is executed by the CPU 20, functioning as the camera control unit 50, the acquisition unit 52, the first export unit 54, the extraction unit 56, the image processing unit 58, and the second export unit 60.

[0042] As an example, such as Figure 8 As shown, with the sheet-like component 92 superimposed on the color developing component 90, the user inputs a photography command via the input device 24. Figure 8 The dashed rectangle represents the shooting range in one photograph. That is, in this embodiment, the shooting range is defined as an area slightly wider than one rectangle of the grid pattern. If the user inputs a shooting command, the photography control unit 50 controls the camera 40 to capture an image with the color developing member 90 and the sheet member 92 overlapping.

[0043] The acquisition unit 52, under the control of the photography control unit 50, acquires an image (hereinafter referred to as "first photographic image") obtained by taking a picture in a state where the color developing member 90 and the sheet member 92 are overlapping, from the camera 40.

[0044] The first derivation unit 54 derives the light attenuation distribution k(x, y) in the first photographic image acquired by the acquisition unit 52 based on the reference signal value data 34 and the signal value of the first photographic image acquired by the acquisition unit 52. In this embodiment, the coordinates are represented by a Cartesian coordinate system with one point of the first photographic image (e.g., the upper left corner) as the origin, the horizontal axis as the x-axis, and the vertical axis as the y-axis. Furthermore, in this embodiment, the light attenuation is represented by a ratio obtained by dividing the light quantity of each coordinate by the light quantity of the coordinate with the highest light quantity.

[0045] The reference signal value data 34 is the signal value of the image (hereinafter referred to as the "second photographic image"): a light attenuation distribution serving as a reference, obtained by photographing the color development unit 90 when the light attenuation is 1 in all coordinates, i.e., the light intensity does not decrease towards the periphery. Furthermore, for each of the multiple saturations, a light attenuation distribution serving as the reference is obtained beforehand. The reference signal value data 34 can also be a function that takes saturation as input and outputs the signal value of the second photographic image corresponding to the input saturation. Furthermore, the reference signal value data 34 can also be a lookup table that establishes a corresponding association between each of the multiple saturations and the signal value of the second photographic image.

[0046] Here, the detailed process of deriving the light attenuation distribution k(x, y) derived by the first deriving unit 54 according to this embodiment will be explained. Here, the signal value of the first photographic image, that is, the pixel value of each pixel of the first photographic image, is set to a value represented by the concentration of the three primary colors of light, namely R, G, and B. The signal value of R SGr(x, y), the signal value of G SGg(x, y), and the signal value of B SGb(x, y) in the first photographic image can be represented by the following equations (1) to (3).

[0047] SGr(x,y)=∑(Sr(λ)*R1(λ,x,y)*illm(λ)*k(x,y))=k(x,y)*[∑(Sr(λ)*R1(λ,x,y)*illm(λ))]……(1)

[0048] SGg(x,y)=∑(Sg(λ)*R1(λ,x,y)*illm(λ)*k(x,y))=k(x,y)*[∑(Sg(λ)*R1(λ,x,y)*illm(λ))]……(2)

[0049] SGb(x,y)=∑(Sb(λ)*R1(λ,x,y)*illm(λ)*k(x,y))=k(x,y)*[∑(Sc(λ)*R1(λ,x,y)*illm(λ))]……(3)

[0050] In equations (1) to (3), the following notation is used.

[0051] λ represents wavelength, and Sr(λ), Sg(λ), and Sc(λ) represent the spectroscopic sensitivities of R, G, and B, respectively.

[0052] R1(λ, x, y) represents the color rendering amount of color rendering component 90.

[0053] illm(λ) represents the spectrum of the illumination light, and k(x,y) represents the light attenuation distribution. As shown in equation (4), i]lm(λ) and k(x,y) are factors obtained by decomposing the illumination distribution illm(λ,x,y).

[0054] il]m(λ,x,y)=Illm(λ)*k(x,y)......(4)

[0055] The first derivation unit 54 in this embodiment calculates the saturation CH(x, y) of each pixel of the first photographic image using the following formula (5).

[0056] CH(x, y)=SGr(x, y) / (SGr(x, y)+SGg(x, y)+SGb(x, y))......(5)

[0057] That is, in this embodiment, the colors used to calculate the saturation CH(x,y) are three colors: R, G, and B. Alternatively, the colors used to calculate the saturation CH(x,y) can be two of R, G, and B, or multiple colors other than R, G, and B. In addition, the reason why the numerator is SGr(x,y) in equation (5) is that in this embodiment, the color rendering component 90 uses red to render the color.

[0058] If equations (1) to (3) are substituted into equation (5), then k(x, y) exists in both the denominator and the numerator. Therefore, k(x, y) is eliminated, and CH(x, y) is represented by the following equation (6).

[0059] CH(x,y)=[∑(Sr(λ)*R1(λ,x,y)*illm(λ))] / ([∑(Sr(λ)*R1(λ,x,y)*illm(λ)) 〕+〔∑(Sg(λ)*R1(λ,x,y)*illm(λ)〕+〔∑(Sb(λ)*R1(λ,x,y)*illm(λ))〕))……(6)

[0060] That is, we can say that CH(x,y) is not affected by k(x,y).

[0061] First, the first derivation unit 54 calculates the saturation of the first photographic image acquired by the acquisition unit 52 according to equation (5). Next, the first derivation unit 54 acquires the signal value of the second photographic image corresponding to the calculated saturation from the reference signal value data 34. As described above, the signal value of this second photographic image is a value obtained in advance based on the light attenuation distribution used as a reference. Furthermore, the first derivation unit 54 divides the signal value of the first photographic image acquired by the acquisition unit 52 by the signal value acquired from the reference signal value data 34. Thus, the first derivation unit 54 derives the light attenuation distribution k(x, y) in the first photographic image acquired by the acquisition unit 52.

[0062] The extraction unit 56 extracts the pattern P based on the light attenuation distribution derived by the first extraction unit 54. The light attenuation distribution derived by the first extraction unit 54 includes the influence of the pattern P in addition to the intensity distribution of the illumination light (i.e., independent of the spectral composition). Therefore, the extraction unit 56 can extract the pattern P based on the differences in the local variation of light attenuation.

[0063] Specifically, the portion of the optical attenuation distribution that changes abruptly, i.e., the high-frequency portion, is considered to be pattern P. In this embodiment, the extraction unit 56 extracts pattern P by applying a high-pass filter. This high-pass filter removes the low-frequency portion with a spatial frequency less than a certain value from the optical attenuation distribution derived by the first extraction unit 54, while allowing the high-frequency portion with a spatial frequency greater than a certain value to pass through.

[0064] Alternatively, the extraction unit 56 can also binarize the light attenuation distribution by threshold processing that changes the threshold of the Otsu binarization method, etc., so that part of the pattern P becomes black and the part outside the pattern P becomes white, thereby extracting the pattern P.

[0065] The image processing unit 58 performs image processing to correct the distortion of the first photographic image based on the pattern P extracted by the extraction unit 56. This image processing can apply known distortion correction techniques.

[0066] The second exporting unit 60 uses the feature data 32 and the first photographic image processed by the image processing unit 58 to export the pressure distribution applied to the color developing unit 90. Specifically, the second exporting unit 60 uses the feature data 32 to convert saturation into a pressure value for each pixel of the first photographic image, thereby exporting the pressure distribution.

[0067] Next, refer to Figure 9 The operation of the image processing apparatus 10 according to this embodiment will be explained. The image processing program 30 is executed by the CPU 20. Figure 9 The pressure measurement process is shown. For example, it is executed when a user inputs a photography command via input device 24. Figure 9 The pressure measurement process is shown.

[0068] exist Figure 9 In step S10, the photography control unit 50 controls the camera 40 to capture an image while the color developing member 90 and the sheet-like member 92 are overlapping. In step S12, the acquisition unit 52, through the control in step S10, acquires from the camera 40 the first photographic image obtained by capturing the image while the color developing member 90 and the sheet-like member 92 are overlapping.

[0069] In step S14, as described above, the first derivation unit 54 derives the light attenuation distribution k(x, y) in the first photographic image acquired in step S12 based on the reference signal value data 34 and the signal value of the first photographic image acquired in step S12. In step S16, as described above, the extraction unit 56 extracts the pattern P based on the light attenuation distribution derived in step S14.

[0070] In step S18, the image processing unit 58 performs image processing to correct the distortion of the first photographic image acquired in step S12 based on the pattern P extracted in step S16. In step S20, the second export unit 60 uses the feature data 32 and the first photographic image processed in step S18 to export the pressure distribution applied to the color developing unit 90. If the processing in step S20 is completed, the pressure measurement process ends.

[0071] As explained above, according to this embodiment, pattern P can be extracted with high precision from an image obtained by capturing an image in which pattern P overlaps with the colored portion of the color-developing component 90. Therefore, pattern P can be used to correct images with high precision. Furthermore, the spectral transmittance of a portion of pattern P is constant at least within the wavelength range of the color used to calculate saturation, and since saturation is determined by the ratio of multiple colors, the influence of pattern P is small in the calculation of saturation. Therefore, pressure distribution can be determined with high precision.

[0072] Furthermore, in the above embodiment, the photography control unit 50 can also control the separate imaging of different regions of the overlapping color developing component 90 and the sheet-like component 92. At this time, the acquisition unit 52 acquires a plurality of first photographic images obtained through this control. Furthermore, the extraction unit 56 extracts a pattern P from each of the plurality of first photographic images. Moreover, the image processing unit 58 performs image processing to synthesize first photographic images representing adjacent regions based on the extracted patterns P. For example, the image processing unit 58 performs image processing on the first photographic images representing adjacent regions so that the patterns P extracted from each of the first photographic images are overlapped and connected, thereby synthesizing first photographic images representing adjacent regions.

[0073] Furthermore, in the above embodiment, the photography control unit 50 can also control the continuous shooting of the overlapping color developing component 90 and sheet-like component 92 in response to a single shooting command from the user, i.e., continuous shooting. At this time, the acquisition unit 52 acquires a plurality of first photographic images obtained through this control. At this time, the extraction unit 56 extracts a pattern P from each of the plurality of first photographic images. Furthermore, the image processing unit 58 generates a shake-corrected first photographic image based on the pattern P extracted for each of the plurality of first photographic images. This shake correction is also known as electronic image stabilization.

[0074] Furthermore, while the above embodiments describe the application of pressure as energy to the object, this is not a limitation. For example, heat or ultraviolet light can also be applied as energy to the object. When heat is applied as energy to the object, the color-developing component 90 can be a THERMOSCALE (trade name) (manufactured by FUJIFILM Corporation) that develops color based on heat. And when ultraviolet light is applied as energy to the object, the color-developing component 90 can be a UVSCALE (trade name) (manufactured by FUJIFILM Corporation) that develops color based on the amount of ultraviolet light.

[0075] Furthermore, in the above embodiments, for example, as the hardware structure of the processing unit that performs various processes like the various functional units of the image processing apparatus 10, various processors as shown below can be used. As described above, in addition to the general-purpose processor, i.e., the CPU, which executes software (programs) and functions as various processing units, the various processors mentioned above also include processors such as FPGAs (Field Programmable Gate Arrays) whose circuit structure can be changed after manufacturing, i.e., Programmable Logic Devices (PLDs), and processors such as ASICs (Application Specific Integrated Circuits) that have specially designed circuit structures for performing specific processes, i.e., dedicated circuits.

[0076] A processing unit can consist of one of these various processors, or it can consist of a combination of two or more processors of the same or different types (e.g., a combination of multiple FPGAs or a combination of a CPU and an FPGA). Furthermore, multiple processing units can also be composed of a single processor.

[0077] As examples of a single processor comprising multiple processing units, firstly, there is the following approach: Represented by client and server computers, a single processor is composed of one or more CPUs and software, functioning as multiple processing units. Secondly, there is the following approach: Represented by System-on-Chip (SoC), a processor that implements the overall system functionality including multiple processing units using a single integrated circuit (IC) chip. In this way, various processing units are constructed using one or more of the aforementioned processors as the hardware structure.

[0078] Furthermore, as the hardware architecture of these various processors, more specifically, it is possible to use circuits composed of circuit elements such as semiconductor elements.

[0079] Furthermore, while the above embodiment describes the image processing program 30 being pre-stored (installed) in the storage unit 22, it is not a limitation. The image processing program 30 may also be provided on a recording medium such as a CD-ROM (Compact Disc Read Only Memory), DVD-ROM (Digital Versatile Disc Read Only Memory), or USB (Universal Serial Bus) memory. Additionally, the image processing program 30 may be downloaded from an external device via a network.

[0080] The invention of Japanese Patent Application No. 2023-043645, filed on March 17, 2023, is incorporated herein by reference in its entirety. Furthermore, all documents, patent applications, and technical standards described in this specification are incorporated herein by reference to the same extent that each document, patent application, and technical standard is specifically and separately described and incorporated herein by reference. Claims (as amended under Article 19 of the Treaty) 1. An image processing apparatus comprising at least one processor, wherein, The processor performs the following processing: A first photographic image is obtained by taking a picture in a state where a color-developing component and a sheet-like component are overlapping. The color-developing component develops color with a saturation distribution corresponding to the applied energy value. The sheet-like component has a first spectral transmittance and is formed with a pattern having a second spectral transmittance that is different from the first spectral transmittance at least in the wavelength range of the color used to calculate saturation. The light attenuation distribution in the acquired first photographic image is derived based on the reference data corresponding to the reference light attenuation distribution and the signal value of the acquired first photographic image; and The pattern is extracted based on the derived optical attenuation distribution. 2. The image processing apparatus according to claim 1, wherein, The second spectral transmittance is lower than the first spectral transmittance. 3. The image processing apparatus according to claim 1 or 2, wherein, The second spectral transmittance is constant within the wavelength range of visible light. 4. The image processing apparatus according to claim 1 or 2, wherein, The processor uses the first photographic image to derive the distribution of energy values ​​applied to the colorimetric component. 5. The image processing apparatus according to claim 1 or 2, wherein, The processor performs image processing to correct the distortion of the first photographic image based on the extracted pattern. 6. The image processing apparatus according to claim 1 or 2, wherein, The processor performs the following processing: Acquire multiple first photographic images obtained by separately photographing different portions of the overlapping color-developing component and the sheet-like component; and The first photographic image representing adjacent partial regions is synthesized based on the extracted pattern. 7. The image processing apparatus according to claim 1 or 2, wherein, The processor performs the following processing: Acquire multiple first photographic images obtained by continuously taking pictures while the color developing component and the sheet-like component are overlapping; and The shake-corrected first photographic image is generated based on the patterns extracted from each of the plurality of first photographic images. 8. The image processing apparatus according to claim 1 or 2, wherein, The processor controls the capture of the first photographic image when the color developing component and the sheet-like component are overlapping. 9. The image processing apparatus according to claim 1 or 2, wherein, The reference data is the signal value of a second photographic image obtained by photographing the color rendering component using a light attenuation distribution that serves as a reference. 10. An image processing method, wherein a processor of an image processing apparatus performs the following processing: A first photographic image is obtained by taking a picture in a state where a color-developing component and a sheet-like component are overlapping. The color-developing component develops color with a saturation distribution corresponding to the applied energy value. The sheet-like component has a first spectral transmittance and is formed with a pattern having a second spectral transmittance that is different from the first spectral transmittance at least in the wavelength range of the color used to calculate saturation. The light attenuation distribution in the acquired first photographic image is derived based on the reference data corresponding to the reference light attenuation distribution and the signal value of the acquired first photographic image; and The pattern is extracted based on the derived optical attenuation distribution. 11. An image processing program for causing a processor in an image processing apparatus to perform the following processing: A first photographic image is obtained by taking a picture in a state where a color-developing component and a sheet-like component are overlapping. The color-developing component develops color with a saturation distribution corresponding to the applied energy value. The sheet-like component has a first spectral transmittance and is formed with a pattern having a second spectral transmittance that is different from the first spectral transmittance at least in the wavelength range of the color used to calculate saturation. The light attenuation distribution in the acquired first photographic image is derived based on the reference data corresponding to the reference light attenuation distribution and the signal value of the acquired first photographic image; and The pattern is extracted based on the derived optical attenuation distribution. 12. (Additionally) The image processing apparatus according to claim 1 or 2, wherein, The saturation is calculated using the ratio of the signal values ​​of each of the various colors in the image.

Claims

1. An image processing apparatus comprising at least one processor, wherein, The processor performs the following processing: A first photographic image is obtained by taking a picture in a state where a color-developing component and a sheet-like component are overlapping. The color-developing component develops color with a saturation distribution corresponding to the applied energy value. The sheet-like component has a first spectral transmittance and is formed with a pattern having a second spectral transmittance that is different from the first spectral transmittance at least in the wavelength range of the color used to calculate saturation. The light attenuation distribution in the first acquired photographic image is derived based on the reference data corresponding to the light attenuation distribution that serves as a reference and the signal value of the acquired first photographic image. and The pattern is extracted based on the derived optical attenuation distribution.

2. The image processing apparatus according to claim 1, wherein, The second spectral transmittance is lower than the first spectral transmittance.

3. The image processing apparatus according to claim 1 or 2, wherein, The second spectral transmittance is constant within the wavelength range of visible light.

4. The image processing apparatus according to claim 1 or 2, wherein, The processor uses the first photographic image to derive the distribution of energy values ​​applied to the colorimetric component.

5. The image processing apparatus according to claim 1 or 2, wherein, The processor performs image processing to correct the distortion of the first photographic image based on the extracted pattern.

6. The image processing apparatus according to claim 1 or 2, wherein, The processor performs the following processing: Acquire multiple first photographic images obtained by separately photographing different portions of the overlapping color-developing component and the sheet-like component; and The first photographic image representing adjacent partial regions is synthesized based on the extracted pattern.

7. The image processing apparatus according to claim 1 or 2, wherein, The processor performs the following processing: Acquire multiple first photographic images obtained by continuously taking pictures while the color developing component and the sheet-like component are overlapping; and The shake-corrected first photographic image is generated based on the patterns extracted from each of the plurality of first photographic images.

8. The image processing apparatus according to claim 1 or 2, wherein, The processor controls the capture of the first photographic image when the color developing component and the sheet-like component are overlapping.

9. The image processing apparatus according to claim 1 or 2, wherein, The reference data is the signal value of a second photographic image obtained by photographing the color rendering component using a light attenuation distribution that serves as a reference.

10. An image processing method, wherein a processor of an image processing apparatus performs the following processing: A first photographic image is obtained by taking a picture in a state where a color-developing component and a sheet-like component are overlapping. The color-developing component develops color with a saturation distribution corresponding to the applied energy value. The sheet-like component has a first spectral transmittance and is formed with a pattern having a second spectral transmittance that is different from the first spectral transmittance at least in the wavelength range of the color used to calculate saturation. The light attenuation distribution in the first acquired photographic image is derived based on the reference data corresponding to the light attenuation distribution that serves as a reference and the signal value of the acquired first photographic image. and The pattern is extracted based on the derived optical attenuation distribution.

11. An image processing program for causing a processor in an image processing apparatus to perform the following processing: A first photographic image is obtained by taking a picture in a state where a color-developing component and a sheet-like component are overlapping. The color-developing component develops color with a saturation distribution corresponding to the applied energy value. The sheet-like component has a first spectral transmittance and is formed with a pattern having a second spectral transmittance that is different from the first spectral transmittance at least in the wavelength range of the color used to calculate saturation. The light attenuation distribution in the first acquired photographic image is derived based on the reference data corresponding to the light attenuation distribution that serves as a reference and the signal value of the acquired first photographic image. and The pattern is extracted based on the derived optical attenuation distribution.

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