Image processing apparatus, image processing method, and program

Abstract

To present, to a user, the reliability of correction using a correction table.SOLUTION: An image processing method includes: acquiring data of a patch scan image obtained by reading a medium onto which a plurality of patch images are output by using a scanner, and data of a color measurement image obtained by measuring the color of the medium by using a color measuring instrument; acquiring the brightness input characteristics of the scanner based on pixel values of the patch images in the patch scan image and color measurement values of the patch images in the color measurement image; for a portion where an error occurs between the brightness input characteristics and brightness ideal characteristics, creating a correction table for correcting the pixel value of a scan image obtained by reading a reading object to a pixel value corresponding to the brightness ideal characteristics; and generating reliability information indicating the reliability of the correction table based on the magnitude of the error.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] This disclosure relates to image correction technology. [Background technology]

[0002] Scanners that read images printed or drawn on paper or other media undergo calibration to ensure faithful reading of the input document. In this calibration process, for example, the color reproduction characteristics of the scanner are first obtained using colorimetric values ​​obtained by measuring multiple patch images printed on the media with a colorimeter and reading values ​​obtained by scanning. Next, a correction table is generated to match the obtained color reproduction characteristics to the required color reproduction characteristics.

[0003] Patent Document 1 discloses a technique for generating a gamma correction table to correct the input characteristics of a printing correction device. The technique disclosed in Patent Document 1 generates a gamma correction table from the minimum to the maximum density value of the scanner by correcting the scanner readings based on known fluctuation errors in the readings. ISO / IEC 24790 also specifies a standard method for generating an OECF (Opto-electronic conversion function) for using a scanner as a measuring instrument for image quality measurement. This OECF is a correction table for linearly correcting the scanner readings with respect to brightness. [Prior art documents] [Patent Documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2017-011601 [Overview of the Initiative] [Problems that the invention aims to solve]

[0005] The correction table for correcting the brightness characteristics of the scanner's reading values depends on the medium on which the patch image used at the time of generating the correction table was printed, or the type of printer, ink, etc. used for the printing. Also, when correcting the brightness characteristics of the reading values obtained by scanning the reading target with the scanner using the correction table, the dynamic range of the brightness of the reading values depends on the medium of the reading target, or the type of printer, ink, etc. used for the printing of the reading target.

[0006] As a result, for example, the dynamic range of the brightness in the reading values of the reading target may be larger than the dynamic range in which the brightness characteristics can be appropriately corrected using the correction table. In this case, the reliability of the corrected brightness characteristics corrected using the correction table becomes low, but the user of the scanner or the user who uses the corrected reading values (hereinafter referred to as "user") cannot recognize that the reliability of the corrected brightness characteristics is low.

Means for Solving the Problem

[0007] In order to solve the above problems, the image processing apparatus according to the present disclosure includes an input characteristic acquisition means for acquiring the brightness input characteristics of the scanner, and reliability information generation means for generating reliability information indicating the reliability of the correction table based on the magnitude of the error that occurs between the brightness input characteristics and the ideal brightness characteristics. The correction table is for correcting the pixel values of the scanned image obtained by scanning the reading target with the scanner to the pixel values corresponding to the ideal brightness characteristics for the portion where an error occurs between the brightness input characteristics and the ideal brightness characteristics.

Effect of the Invention

[0008] According to the present disclosure, it is possible to present to the user the reliability of the correction using the correction table for correcting the pixel values of the image obtained by reading with the scanner.

Brief Description of the Drawings

[0009] [Figure 1]This is a block diagram showing an example of the functional configuration of an image processing apparatus according to Embodiment 1. [Figure 2] This is a block diagram showing an example of the hardware configuration of an image processing device according to Embodiment 1. [Figure 3] This is an explanatory diagram illustrating an example of a patch image according to Embodiment 1. [Figure 4] (a) is an explanatory diagram illustrating an example of the brightness input characteristics according to Embodiment 1. (b) is an explanatory diagram illustrating another example of the brightness input characteristics according to Embodiment 1. [Figure 5] This is an explanatory diagram illustrating an example of a correction table and reliability information related to Embodiment 1. [Figure 6] This flowchart shows an example of the processing flow of the image processing apparatus according to Embodiment 1. [Figure 7] (a) is a flowchart showing the details of the process in S630 shown in Figure 6. (b) is a flowchart showing the details of the process in S640 shown in Figure 6. (c) is a flowchart showing the details of the process in S650 shown in Figure 6. [Figure 8] This is a block diagram showing an example of the functional configuration of an image processing apparatus according to Embodiment 2. [Figure 9] This flowchart shows an example of the processing flow of the image processing apparatus according to Embodiment 2. [Modes for carrying out the invention]

[0010] The embodiments of this disclosure will be described in detail below with reference to the attached drawings. Note that the configurations shown in the following embodiments are merely examples and do not limit the scope of this disclosure to these configurations alone. Furthermore, not all combinations of configurations shown in the following embodiments are necessarily essential to this disclosure.

[0011] [Embodiment 1] The image processing apparatus 100 according to Embodiment 1 will be described with reference to Figures 1 to 7. The image processing apparatus 100 generates a correction table for correcting the pixel values ​​of a scanned image (hereinafter referred to as the "target scanned image") obtained by reading a target object. Figure 1 is a block diagram showing an example of the functional configuration of the image processing apparatus 100 according to Embodiment 1. The image processing apparatus 100 includes a scan acquisition unit 110, a color measurement acquisition unit 111, an input characteristic acquisition unit 120, a correction table generation unit 130, a reliability information generation unit 140, and an output unit 190. In addition to the above configuration, the image processing apparatus 100 may also include a range acquisition unit 160 or an approximation function acquisition unit 170. Hereinafter, the image processing apparatus 100 will be described as including a range acquisition unit 160 and an approximation function acquisition unit 170.

[0012] The processing of each component of the image processing device 100 is performed by hardware such as an ASIC (Application Specific Integrated Circuit) built into the image processing device 100. This processing may also be performed by hardware such as an FPGA (Field Programmable Gate Array). Alternatively, this processing may be performed by software using memory such as RAM (Random Access Memory) and a processor such as a CPU (Central Processor Unit). Details of the processing of each component of the image processing device 100 will be described later.

[0013] Here, with reference to Figure 2, the hardware configuration of the image processing device 100 according to Embodiment 1 will be described when each part of the image processing device 100 operates as software. Figure 2 is a block diagram showing an example of the hardware configuration of the image processing device 100 according to Embodiment 1. The image processing device 100 is composed of a computer, which has a CPU 211, ROM 212, RAM 213, auxiliary storage device 214, display unit 215, operation unit 216, communication unit 217, and bus 218, as shown as an example in Figure 2.

[0014] The CPU 211 is a processor that controls the computer using programs or data stored in the ROM 212 or RAM 213, thereby enabling the computer to function as a component of the image processing device 100 shown in Figure 1. The image processing device 100 may have one or more dedicated hardware components separate from the CPU 211, and at least a portion of the processing performed by the CPU 211 may be executed by the dedicated hardware. Examples of dedicated hardware include ASICs, FPGAs, and DSPs (Digital Signal Processors). The ROM 212 is a memory that stores programs and the like that do not require modification. The RAM 213 is a memory that temporarily stores programs or data supplied from the auxiliary storage device 214, or data supplied from the outside via the communication unit 217. The auxiliary storage device 214 is configured, for example, as a hard disk drive and stores various types of data such as image data or audio data.

[0015] The display unit 215 is composed of, for example, a liquid crystal display or LEDs, and displays a GUI (Graphical User Interface) for the user to operate the image processing device 100 or to view the processing status in the image processing device 100. The operation unit 216 is composed of, for example, a keyboard, mouse, joystick, or touch panel, and receives various instructions from the user and inputs them to the CPU 211. The CPU 211 also operates as a display control unit that controls the display unit 215, and as an operation control unit that controls the operation unit 216.

[0016] The communication unit 217 is used for communication between the image processing device 100 and external devices. For example, if the image processing device 100 is connected to an external device by a wired connection, a communication cable is connected to the communication unit 217. If the image processing device 100 has a function for wireless communication with an external device, the communication unit 217 is equipped with an antenna. The bus 218 connects the various parts of the image processing device 100 to transmit information. In Embodiment 1, the display unit 215 and the operation unit 216 are described as being located inside the image processing device 100, but at least one of the display unit 215 and the operation unit 216 may be located outside the image processing device 100 as a separate device.

[0017] The scan acquisition unit 110 acquires data of an image (hereinafter referred to as "patch scan image") obtained by reading a medium (hereinafter referred to as "patch original") on which multiple patch images with different brightness or color components are formed. The medium is made up of, for example, paper, a resin plate, or a glass plate. Formation as used here refers to a state in which printing or drawing is done on a medium such as paper. Hereinafter, the patch original will be described as a paper medium on which the above-mentioned patch images are printed. The image processing device 100 controls the scanner 10 based on user operation, for example, to cause the scanner 10 to read the patch original and output the data of the patch scan image (hereinafter referred to as "patch scan data") which is the reading result. The scan acquisition unit 110 acquires the patch scan data output by the scanner 10 from the scanner 10.

[0018] Scanner 10 is an image input device composed of an image scanner or the like, which converts an image read by an image sensor such as a solid-state image sensor into electrical signal data and outputs it. Scanner 10 may be a single-function image scanner or a copier or multifunction device that also has other functions such as printing, as long as it is capable of outputting patch scan data obtained by reading a patch document. The source from which the scan acquisition unit 110 acquires patch scan data does not necessarily have to be scanner 10. For example, scan acquisition unit 110 may acquire patch scan data from storage device 12, which has patch scan data stored in it in advance. Here, storage device 12 is composed of a hard disk drive or the like, which holds the written data and is capable of reading the held data.

[0019] The colorimetric acquisition unit 111 acquires colorimetric image data (hereinafter referred to as "colorimetric data") obtained by measuring the color of the patch original using the colorimeter 11. The colorimeter 11 may be of the direct stimulus value reading type or of the so-called spectrophotometer type. The colorimetric acquisition unit 111 may acquire the colorimetric data output by the colorimeter 11 directly from the colorimeter 11, or it may acquire the colorimetric data from the storage device 12 by reading the colorimetric data from the storage device 12 in which the colorimetric data is stored in advance.

[0020] The patch image will be explained with reference to Figure 3. Figure 3 is a diagram showing an example of a patch image according to Embodiment 1, and is an explanatory diagram for explaining the patch image. As an example, Figure 3 shows a grayscale patch image (hereinafter referred to as "gray patch image") in which multiple gray patch images have equally spaced differences in brightness between adjacent gray patch images. Hereafter, the patch original will be described as a piece of paper on which the multiple gray patch images shown as an example in Figure 3 are printed. Note that the patch original is not limited to a printed gray patch image, but may be a piece of paper on which multiple patch images with different brightness or color components are output, or a piece of paper on which multiple color patch images with color are output. Also, as an example, Figure 3 shows a total of 16 gray patch images arranged in a row of 4 vertically and 4 horizontally in Figure 3, but the number and arrangement of gray patch images are not limited to this. Note that in Figure 3, patch image 310 is the patch image with the largest brightness value among the multiple patch images, that is, the patch image that is closest to white. Furthermore, patch image 311 is the patch image with the lowest brightness value among the multiple patch images, that is, the patch image that is closest to black.

[0021] Hereinafter, the scan acquisition unit 110 will be described as acquiring patch scan data in which the readings of each pixel are represented as pixel values ​​in the RGB color system. Specifically, the patch scan data acquired by the scan acquisition unit 110 will be described as in which the readings of each pixel are represented as 16-bit wide pixel values ​​for each of the R (red), G (green), and B (blue) color components. Furthermore, the color measurement acquisition unit 111 will be described as acquiring color measurement data in which the measured color values ​​are represented in the XYZ color system.

[0022] The input characteristics acquisition unit 120 acquires the brightness input characteristics of the scanner 10 that read the patch original based on the pixel values ​​in each patch image within the patch scan image and the colorimetric values ​​in each patch image within the colorimetric image. Specifically, for example, first, the input characteristics acquisition unit 120 acquires the pixel values ​​in each patch image within the patch scan image. For example, for each patch image, the input characteristics acquisition unit 120 calculates the average value of the pixel values ​​of all pixels included in at least a predetermined portion of the patch image area 320 (the area enclosed by the dashed line shown in Figure 3), and acquires the average value as the pixel value of the patch image. By using the average value of the pixel values ​​in at least a portion of the patch image area as the pixel value of the patch image, it is possible to acquire a pixel value that has been smoothed out to the effects caused by printing inconsistencies in the patch original, or reading errors or noise when reading the patch image. Note that the pixel value in each patch image is not limited to the average value of the pixel values ​​of all pixels included in the area 320, as long as it can smooth out the above-mentioned effects. For example, the pixel values ​​in each patch image may be other statistical values ​​that are different from the mode or median, or other mean values, of the pixel values ​​of pixels included in at least a portion of the patch image region.

[0023] If the brightness of patch image 310 is less than the brightness of an area that is not part of any of the multiple patch images (hereinafter referred to as the "out-of-patch area"), it is preferable for the input characteristic acquisition unit 120 to also acquire the pixel values ​​of the out-of-patch area. When acquiring the pixel values ​​of the out-of-patch area, for example, the input characteristic acquisition unit 120 acquires the pixel values ​​of the out-of-patch area by calculating the average value of all pixels contained in area 322, which is the same size as or approximately the same size as area 320 and is enclosed by a dashed line in Figure 3. Note that in Figure 3, area 322 is not shown with a frame like that around the patch images, but area 322 may be enclosed with a frame like that around the patch images to clearly indicate the area from which to acquire pixel values ​​in the out-of-patch area.

[0024] Here, the input characteristic acquisition unit 120 may acquire one color component value from the RGB color component values ​​in the pixel value (hereinafter referred to as "color component value") for each patch image, or it may acquire multiple color component values. Alternatively, the input characteristic acquisition unit 120 may acquire all RGB color component values ​​for each patch image and calculate the luminance value using the acquired color component values ​​to obtain the luminance value for each patch image. The luminance value can be calculated, for example, by the following equation (1). Y = 0.2126R + 0.7152G + 0.0722B …Equation (1)

[0025] Here, Y is the luminance value, R is the value of the red component in the pixel value (hereinafter referred to as the "red component value"), G is the value of the green component in the pixel value (hereinafter referred to as the "green component value"), and B is the value of the blue component in the pixel value (hereinafter referred to as the "blue component value"). Hereafter, the red component value, green component value, blue component value, and luminance value corresponding to each patch image and region 322 will be denoted as R(p), G(p), B(p), and Y(p), and will be explained. Here, p is information for identifying each patch image and region 322, and is a value such as a non-negative integer associated with each patch image and region 322.

[0026] Next, the input characteristic acquisition unit 120 acquires the luminance component value of the colorimetric value in each patch image within the colorimetric image (hereinafter referred to as "colorimetric luminance value"). When acquiring the colorimetric luminance value, the input characteristic acquisition unit 120 may calculate the average value of the colorimetric value using multiple colorimetric values ​​acquired at multiple locations in at least a portion of the patch image area 320 for each patch image, and acquire the calculated average value as the colorimetric luminance value. By acquiring the colorimetric luminance value using the average value of the colorimetric values ​​acquired at multiple locations in the patch image area, it is possible to acquire a colorimetric luminance value that has been smoothed out to the effects caused by printing irregularities in the patch original, or errors or noise when measuring the color of the patch image. Note that the colorimetric luminance value in each patch image is not limited to a colorimetric luminance value based on the average value of the colorimetric value, as long as it can smooth out the above-mentioned effects. For example, the colorimetric luminance value in each patch image may be based on other statistical values ​​different from the average value, such as the mode or median of the colorimetric values ​​acquired at multiple locations in the patch image area. Hereinafter, the colorimetric luminance value corresponding to each patch image is Y S (p) is used for explanation. Next, the input characteristic acquisition unit 120 acquires the color component values ​​R(p), G(p), or B(p), or the luminance value Y(p) in each patch image within the patch scan image, and the measured color luminance value Y in each patch image within the colorimetric image. S The relationship with (p) is obtained as a brightness input characteristic.

[0027] The input characteristic acquisition unit 120 then obtains G(p), which is the green component value in each patch image within the patch scan image, and Y, which is the measured color intensity value in each patch image within the colorimetric image. S The relationship with (p) will be described as being acquired as a brightness input characteristic. The brightness input characteristic acquired by the input characteristic acquisition unit 120 is G(p), which is the green component value in each patch image within the patch scan image, and Y, which is the measured colorimetric luminance value in each patch image within the colorimetric image. S The relationship is not limited to (p). The brightness input characteristics are R(p) or B(p), which are the red or blue component values ​​in each patch image within the patch scan image, or the luminance value Y(p) calculated using each color component value, and the colorimetric luminance value Y SThe relationship may also be with (p). The input characteristic acquisition unit 120 can reduce the amount of computation by using the green component value in each patch image within the patch scan image when acquiring brightness input characteristics, compared to the case where brightness values ​​calculated based on all color component values ​​are used. Furthermore, the input characteristic acquisition unit 120 can acquire high-precision brightness input characteristic accuracy by using the green component value in each patch image within the patch scan image when acquiring brightness input characteristics, compared to the case where red component values ​​or blue component values ​​are used. This is because the influence of the green component on brightness is greater than the influence of the red or blue component on brightness.

[0028] Furthermore, the input characteristic acquisition unit 120 may approximate the relationship using an approximation function and acquire the approximate input characteristic obtained from this approximation as the brightness input characteristic. Specifically, for example, the approximate input characteristic acquired by the input characteristic acquisition means is a linear approximation of the relationship using a linear approximation function. The input characteristic acquisition unit 120 calculates the linear approximation function using, for example, the least squares method. Note that linear approximation of the relationship using a linear approximation function is just one example, and the approximate input characteristic may be a curved approximation using a polynomial. By using the approximate input characteristic approximated by the approximation function as the brightness input characteristic, it is possible to acquire a brightness input characteristic that suppresses the effects of reading errors or noise that occur when reading the patch image, or individual differences in the sensor used to read the patch image.

[0029] Referring to Figure 4, the brightness input characteristics acquired by the input characteristic acquisition unit 120 will be explained. Figures 4(a) and (b) are explanatory diagrams illustrating an example of the brightness input characteristics acquired by the input characteristic acquisition unit 120 according to Embodiment 1. Specifically, Figures 4(a) and (b) are diagrams illustrating an example of the relationship between the green component value in each patch image within the patch scan image and the measured colorimetric luminance value in each patch image within the colorimetric image. In Figures 4(a) and (b), the horizontal axis represents the magnitude of the luminance component value (measured colorimetric luminance value) of the measured colorimetric value in each patch image within the colorimetric image, and the vertical axis represents the magnitude of the green component value (green component value) of the pixel value in each patch image within the patch scan image. The horizontal axis shows the minimum value of the measured colorimetric luminance value that the colorimeter 11 can output, normalized to a minimum value of 100. The vertical axis shows the green component value from 0 to 65535, as the green component value is represented by a 16-bit width.

[0030] In Figures 4(a) and (b), the white triangles (△) in the center represent G(p), which is the green component value of the patch image in the patch scan image, and Y, which is the colorimetric luminance value of the patch image in the corresponding colorimetric image. S These are points plotted in correspondence with (p). The solid lines represent the approximate lines obtained by linearly approximating the positions of the multiple triangles shown in Figures 4(a) and (b) using a linear approximation function, and show the approximate input characteristics. For example, the input characteristic acquisition unit 120 linearly approximates the positions of the multiple triangles by acquiring an approximate line that minimizes the mean square of the distance from the approximate line to each triangle's position. Similarly, the dashed lines represent the approximate curves obtained by curvely approximating the positions of the multiple triangles shown in Figures 4(a) and (b) using a polynomial, and show the approximate input characteristics. The approximate curves shown in Figures 4(a) and (b) are, as an example, approximations of the positions of the multiple triangles using a quartic function. For example, the input characteristic acquisition unit 120 approximates the positions of the multiple triangles using a quartic function by acquiring an approximate curve that minimizes the mean square of the distance from the approximate curve to each triangle's position.

[0031] Furthermore, in Figures 4(a) and (b), the dashed lines represent the ideal brightness input characteristics (hereinafter referred to as "ideal brightness characteristics"). Assuming that the colorimetric values ​​of the colorimetric image acquired by the colorimetric acquisition unit 111 are ideal values ​​(hereinafter referred to as "ideal values"), in the ideal brightness characteristics, the colorimetric luminance value and the RGB color component values ​​obtained from the colorimetric value are directly proportional. Specifically, for example, as shown in Figures 4(a) and (b), in the ideal brightness characteristics, when the colorimetric luminance value is the minimum value of 0, the RGB color component values ​​become 0, and when the colorimetric luminance value is the maximum value of 100, the RGB color component values ​​become 65535. That is, the ideal brightness characteristics corresponding to Figures 4(a) and (b) are given by the following equation (2). G = Y / 100 × (Maximum value of green component) Equation (2) Here, the "maximum value of the green component" is, for example, 65535 if the bit width representing the green component value is 16 bits.

[0032] The correction table generation unit 130 generates a correction table for correcting the pixel values ​​of the target scanned image to pixel values ​​corresponding to the ideal brightness characteristics for portions where errors occur between the brightness input characteristics and the ideal brightness characteristics of the image input device 100. First, the correction table generation unit 130 converts the measured color values ​​to the values ​​of the RGB color system using, for example, the following equation (3), based on the values ​​of each component of the measured color values ​​using the XYZ color system. R = 3.2410X - 1.5374Y - 0.4986Z G =-0.9692X + 1.8760Y + 0.0416Z…Equation (3) B = 0.0556X - 0.2040Y + 1.0507Z Here, X, Y, and Z are the values of the X component, Y component, and Z component in the XYZ color system. In Equation (3), X, Y, and Z are not the values normalized from 0 to 100 for the values of the X component, Y component, and Z component, but values having the same bit width as the pixel values in the RGB color system acquired by the scan acquisition unit 110. Since the colorimetric values are ideal values as described above, each of the RGB color component values calculated by Equation (2) or the like based on the colorimetric values becomes an ideal value. Hereinafter, the RGB color component values calculated based on the colorimetric values in each patch image are denoted as R i (p), G i (p), and B i (p) and will be described. The correction table generation unit 130 generates a correction table associating R(p), G(p), and B(p) with R i (p), G i (p), and B i (p).

[0033] The correction table generation unit 130 may generate a correction table for correcting a portion where an error occurs between the approximate input characteristic as the lightness input characteristic and the lightness ideal characteristic. In this case, for example, the correction table generation unit 130 replaces the pixel values in each patch image in the patch scan image with approximate values approximated by a linear approximation function, and generates a correction table so that the approximate values are corrected to the pixel values corresponding to the lightness ideal characteristic. By generating a correction table such that the approximate values approximated by the linear approximation function are corrected to the pixel values corresponding to the lightness ideal characteristic, it is possible to generate a correction table that suppresses the influence caused by reading errors or noise generated during the reading of the patch image.

[0034] The approximation function acquisition unit 170 acquires an approximation function different from the linear approximation function used by the input characteristic acquisition unit 120 when acquiring the approximate input characteristics. Specifically, the approximation function acquisition unit 170 acquires an approximation function that approximates the relationship between the pixel value in each patch image in the patch scan image, or the brightness value calculated based on the pixel value, and the colorimetric brightness value in each patch image in the colorimetric image using a polynomial. If the image processing device 100 includes the approximation function acquisition unit 170, the correction table generation unit 130 may generate a correction table as follows for the portion where an error occurs between the approximate input characteristics, which are brightness input characteristics approximated by a linear approximation function, and the brightness ideal characteristics. Specifically, first, the correction table generation unit 130 replaces the pixel value in each patch image in the patch scan image with an approximate value approximated by the polynomial approximation function acquired by the approximation function acquisition unit 170. Next, the correction table generation unit 130 generates a correction table so that the approximate value is corrected to the pixel value corresponding to the brightness ideal characteristics. By generating a correction table in this manner, it is possible to generate a correction table that suppresses the effects caused by reading errors or noise that occur during the reading of the patch image. Furthermore, by generating a correction table in this manner, it is possible to generate a correction table that suppresses the effects caused by differences between scanners 10 that read the patch original. In Figures 4(a) and (b), the approximation function obtained by the approximation function acquisition unit 170 is shown as an example by the approximation curve indicated by the dashed line.

[0035] The reliability information generation unit 140 generates information indicating the reliability of the correction table based on the magnitude of the error between the brightness input characteristic and the brightness ideal characteristic. The reliability information generation unit 140 may also generate information indicating the reliability of the correction table based on the magnitude of the error between the approximate input characteristic used as the brightness input characteristic and the brightness ideal characteristic. The range acquisition unit 160 acquires the range of pixel values ​​in the patch scan image, or the range of luminance values ​​calculated based on said pixel values ​​(hereinafter, the range of pixel values ​​and the range of luminance values ​​are collectively referred to as the "range of pixel values, etc."). Specifically, for example, the range acquisition unit 160 acquires the minimum and maximum values ​​of the pixel values ​​or luminance values ​​in the patch scan image, and acquires the range corresponding to the minimum and maximum values ​​as the range of pixel values, etc. in the patch scan image.

[0036] The reliability information generation unit 140 generates reliability information indicating high reliability of the correction table when the error between the brightness input characteristic or approximate input characteristic and the brightness ideal characteristic is below a predetermined threshold over the entire range of pixel values, etc., acquired by the range acquisition unit 160. Specifically, the reliability information in this case indicates high reliability of the correction table over the entire range of pixel values ​​or brightness values ​​that the target scanned image can take. Here, the case where the error between the brightness input characteristic or approximate input characteristic and the brightness ideal characteristic is below a predetermined threshold over the entire range of pixel values, etc., acquired by the range acquisition unit 160 is, for example, the brightness input characteristic shown in Figure 4(a). In the brightness input characteristic shown in Figure 4(a), the brightness input characteristic or approximate input characteristic and the brightness ideal characteristic are close over the entire range of pixel values, etc., acquired by the range acquisition unit 160. In such cases, the reliability information generation unit 140 generates reliability information indicating that the correction table is highly reliable not only for the range of pixel values, etc., acquired by the range acquisition unit 160, but also for areas outside that range.

[0037] Furthermore, the reliability information generation unit 140 generates reliability information indicating low reliability of the correction table when the error between the brightness input characteristic or approximate input characteristic and the brightness ideal characteristic is greater than a predetermined threshold within the range acquired by the range acquisition unit 160. Specifically, in this case, the reliability information generation unit 140 generates reliability information indicating low reliability for the range of pixel values ​​or brightness values ​​that the target scan image can take, which is not included in the range acquired by the range acquisition unit 160. In addition, in this case, the reliability information generation unit 140 may generate reliability information by adding information indicating high reliability of the correction table for the range of pixel values ​​or brightness values ​​that the target scan image can take, which is included in the range acquired by the range acquisition unit 160. Furthermore, when generating reliability information indicating low reliability, the reliability information generation unit 140 may generate reliability information by adding information indicating that the reliability of the correction table is lower the further away it is from the range acquired by the range acquisition unit 160.

[0038] Here, a case where the error between the brightness input characteristic or approximate input characteristic and the ideal brightness characteristic within the range of pixel values ​​acquired by the range acquisition unit 160 is greater than a predetermined threshold is, for example, the brightness input characteristic shown in Figure 4(b). In the brightness input characteristic shown in Figure 4(b), the brightness input characteristic shows a large discrepancy between the brightness input characteristic or approximate input characteristic and the ideal brightness characteristic within the range of pixel values ​​acquired by the range acquisition unit 160, compared to the brightness input characteristic shown in Figure 4(a). In such a case, for example, the reliability information generation unit 140 generates reliability information indicating that the reliability of the correction table is high for the range of pixel values ​​acquired by the range acquisition unit 160, and that the reliability of the correction table is low outside of that range. The brightness input characteristic shown in Figure 4(b) occurs, for example, when the scanner 10 that reads the patch image performs gamma correction on the readings of the patch image, and the scanner 10 outputs the gamma-corrected readings as patch scan data. Because it is difficult to accurately predict and correct pixel values ​​outside the range acquired by the range acquisition unit 160 based on the gamma-corrected readings, the reliability of the correction table is low for values ​​outside that range.

[0039] The confidence information generated by the confidence information generation unit 140 is, for example, information indicating a highly reliable interval (hereinafter referred to as the "confidence interval"), that is, information indicating a range of highly reliable pixel values, etc. In this case, for example, it indicates that intervals other than the confidence interval are less reliable intervals. The confidence information may also be information indicating a less reliable interval (an interval other than the confidence interval), that is, information indicating a range of less reliable pixel values, etc. In this case, for example, it indicates that intervals other than the less reliable interval are highly reliable intervals (confidence intervals).

[0040] The output unit 190 outputs the correction table generated by the correction table generation unit 130 and the reliability information generated by the reliability information generation unit 140. Specifically, for example, the correction table and reliability information are output to the storage device 12, and the output correction table and reliability information are stored in the storage device 12. The correction table and reliability information output by the output unit 190 will be explained with reference to Figure 5. Figure 5 is an explanatory diagram for illustrating an example of the correction table and reliability information output by the output unit 190 according to Embodiment 1. The correction table and reliability information shown in Figure 5 are described using a single markup language, with the information corresponding to the correction table and the information corresponding to the reliability information being described. For example, as shown as an example in Figure 5, the reliability information generated by the reliability information generation unit 140 is appended to a file containing the correction table data generated by the correction table generation unit 130. By storing the correction table data and reliability information in a single file in this way, the generated correction table and the sections with high or low reliability in the correction table can be managed in association. Furthermore, if the correction table and the reliability information are managed in association, it is not necessary to put the correction table data and the reliability information into a single file; they can be stored in separate files.

[0041] Figure 5 shows the minimum and maximum values ​​of the range of highly reliable luminance values ​​as confidence interval information in the section labeled "Confidence Information." In other words, the confidence information shown in Figure 5 indicates that the correction table is highly reliable within the range between the minimum and maximum values, and that the table is less reliable within the range smaller than the minimum value and larger than the maximum value. The minimum and maximum values ​​shown in Figure 5 are the minimum and maximum values ​​of the luminance value Y(p), which is calculated using, for example, equation (1), based on the color component values ​​R(p), G(p), and B(p) of the pixel values ​​of each patch image. More specifically, the minimum and maximum values ​​shown as an example in Figure 5 are the minimum and maximum values ​​when Y(p), calculated using equation (1) based on R(p), G(p), and B(p), is normalized to a value from 0 to 100. Note that these minimum and maximum values ​​are not limited to those normalized to a value from 0 to 100. For example, these minimum and maximum values ​​may be the minimum and maximum values ​​of Y(p) calculated using, for example, equation (1), based on R(p), G(p), and B(p). Alternatively, a highly reliable range may be expressed using the minimum and maximum values ​​of each color component, i.e., the minimum and maximum values ​​of R(p), G(p), and B(p).

[0042] Furthermore, in Figure 5, the section labeled "Correction Table" shows six numbers arranged horizontally. Of these six numbers, the three on the left correspond to the sets of R(p), G(p), and B(p) values ​​for each color component in each patch image. The three numbers on the right are the ideal values ​​corresponding to R(p), G(p), and B(p). i (p), G i (p), and B i (p) corresponds to (p). However, in the correction table shown in Figure 5, the three numbers on the right are R i (p), G i (p), and B iEach value in (p) is a numerical value normalized to a value between 0 and 100. In the correction table, normalizing the three numbers on the right to values ​​between 0 and 100 is just one example; they may also be normalized to values ​​between 0 and 1. Alternatively, the three numbers on the right may be represented using values ​​corresponding to the bit width of each color component value, for example, values ​​from 0 to 65535.

[0043] The operation of the image processing apparatus 100 will be described with reference to Figures 6 and 7. In the following description, the symbol "S" represents a step. Figure 6 is a flowchart showing an example of the processing flow of the image processing apparatus 100 according to Embodiment 1. Figure 7(a) is a flowchart showing the details of the processing S630 shown in Figure 6, Figure 7(b) is a flowchart showing the details of the processing S640 shown in Figure 6, and Figure 7(c) is a flowchart showing the details of the processing S650 shown in Figure 6.

[0044] First, in S610, the colorimetric acquisition unit 111 acquires colorimetric data. Next, in S620, the scan acquisition unit 110 acquires patch scan data. The order of processing in S610 and S620 is arbitrary. Next, in S630, the input characteristic acquisition unit 120 acquires the brightness input characteristics. Now, referring to Figure 7(a), the processing in S630 will be explained. After S620, in S631, the input characteristic acquisition unit 120 acquires the green component values ​​of the pixel values ​​of multiple pixels in the patch image for each patch image and calculates the average value of the acquired green component values. After S631, in S632, the input characteristic acquisition unit 120 calculates the average value of the colorimetric luminance values ​​in the patch image for each patch image. After S632, in S633, the input characteristic acquisition unit 120 acquires the approximate input characteristics by linear approximation using a linear approximation function and acquires the acquired approximate input characteristics as the brightness input characteristics. After S633, the image processing device 100 completes the processing shown in the flowchart in Figure 7(a) and then completes the processing of S630.

[0045] After S630, in S640, the correction table generation unit 130 generates a correction table. Now, referring to Figure 7(b), the process of S640 will be explained. After S630, in S641, the approximation function acquisition unit 170 acquires an approximation function that approximates the curve using a polynomial. After S641, in S642, the correction table generation unit 130 generates a correction table so that the approximation value approximated by the polynomial approximation function is corrected to a pixel value corresponding to the ideal brightness characteristic. After S642, the image processing device 100 completes the process of S640 by completing the flowchart shown in Figure 7(b). After S640, in S650, the reliability information generation unit 140 generates reliability information. Now, referring to Figure 7(c), the process of S650 will be explained. After S640, in S651, the reliability information generation unit 140 determines whether the error between the brightness input characteristic and the ideal brightness characteristic is greater than a threshold. If, in S651, it is determined that the error is not greater than the threshold, that is, if the error is less than or equal to the threshold, then in S652, the reliability information generation unit 140 generates reliability information indicating that the correction table is highly reliable.

[0046] If, in S651, the error is determined to be greater than the threshold, in S653, the range acquisition unit 160 acquires the range of pixel values, etc., in the patch scan image. Specifically, the range acquisition unit 160 acquires the minimum and maximum values ​​of the green component. The range acquisition unit 160 may, instead of acquiring the minimum and maximum values ​​of the green component, acquire an approximate minimum value obtained by approximating the minimum value using a linear approximation function as the minimum value of the green component, and acquire an approximate maximum value obtained by approximating the maximum value using a linear approximation function as the maximum value of the green component. After S653, in S654, the reliability information generation unit 140 generates reliability information indicating that the range not included in the range from the minimum value to the maximum value is unreliable. After S652 or S654, the image processing device 100 completes the processing of the flowchart shown in Figure 7(c) and completes the processing of S650. After S650, in S660, the output unit 190 outputs the correction table generated by the correction table generation unit 130 and the reliability information generated by the reliability information generation unit 140. After S660, the image processing device 100 completes the process shown in the flowchart in Figure 6.

[0047] The image processing device 100 configured as described above can generate reliability information that enables the user to be presented with the reliability of the correction using the correction table. Furthermore, the reliability information generated by the image processing device 100 makes it easy to determine whether the scanner 10 is a device that outputs pixel value data linear with respect to brightness or a device that outputs pixel value data after gamma correction. In addition, the image processing device 100 can generate a correction table that suppresses the effects caused by reading errors or noise that occur when reading the patch image. Note that the ease of predicting the pixel value after removing reading errors or noise differs depending on whether the scanner 10 outputs linearly with respect to brightness or not. Therefore, it is preferable to append the reliability information to the file containing the correction table data, and store the correction table data and the reliability information in a single file, thereby managing the correction table in association with the sections in the correction table that have high or low reliability.

[0048] [Embodiment 2] The image processing apparatus 800 according to Embodiment 2 will be described with reference to Figures 8 and 9. The image processing apparatus 800 corrects the pixel values ​​of a scanned image (target scanned image) obtained by reading a target object using a correction table generated by the image processing apparatus 100 according to Embodiment 1, etc. Figure 8 is a block diagram showing an example of the functional configuration of the image processing apparatus 800 according to Embodiment 2. The image processing apparatus 800 includes a scan acquisition unit 810, a correction table acquisition unit 820, a reliability information acquisition unit 821, a correction unit 830, and an output control unit 890. In addition to the above configuration, the image processing apparatus 800 may also include a reliability determination unit 840, an evaluation area acquisition unit 850, or an evaluation unit 860, etc. Hereinafter, the image processing apparatus 800 will be described as including a reliability determination unit 840, an evaluation area acquisition unit 850, and an evaluation unit 860.

[0049] The processing of each component of the image processing device 800 is performed by hardware such as an ASIC or FPGA built into the image processing device 800. Alternatively, this processing may be performed by software using memory such as RAM and a processor such as a CPU or GPU. When each component of the image processing device 800 operates as software, for example, the image processing device 800 is configured as a computer having the hardware shown as an example in Figure 2.

[0050] The scan acquisition unit 810 acquires data of the target scan image obtained by reading the object to be read (hereinafter referred to as "target scan data"). The image processing device 800 controls the scanner 80, for example, based on user operation, to cause the scanner 80 to read the object to be read and output the target scan data, which is the reading result. The scan acquisition unit 810 acquires the target scan data output by the scanner 80 from the scanner 80.

[0051] The scanner 80 is a device composed of an image scanner or the like, which converts an image read by an image sensor such as a solid-state image sensor into electrical signal data and outputs it. The scanner 80 may be a single-function image scanner, a copier or multifunction device that also has other functions such as printing, as long as it is capable of outputting target scan data obtained by reading the object to be read. The source from which the scan acquisition unit 810 acquires the target scan data does not necessarily have to be the scanner 80. For example, the scan acquisition unit 810 may acquire the target scan data from the storage device 12, which has the target scan data stored in it in advance. The storage device 12 has been described in Embodiment 1, so its description will be omitted. Note that the scanner 80 may be the same as the scanner 10 shown in Figure 1, a different unit of the same model as the scanner 10, or a different model from the scanner 10.

[0052] Hereinafter, the scan acquisition unit 810 will be described as acquiring target scan data in which the reading value of each pixel is represented as a pixel value in the RGB color system. Specifically, the target scan data acquired by the scan acquisition unit 810 will be described as in which the reading value of each pixel is represented as a 16-bit wide pixel value for each of the R (red), G (green), and B (blue) color components.

[0053] The correction table acquisition unit 820 acquires a correction table for correcting the pixel values ​​of the target scanned image. Specifically, the correction table acquisition unit 820 acquires the correction table by reading a correction table that has been previously stored in the storage device 12 or the like. The correction table is generated by the image processing device 100 or the like according to Embodiment 1, and is shown as an example in Figure 5. The reliability information acquisition unit 821 acquires reliability information indicating the reliability of the correction table. Specifically, the reliability information acquisition unit 821 acquires reliability information by reading reliability information that has been previously stored in the storage device 12 or the like. The reliability information is generated by the image processing device 100 or the like according to Embodiment 1, and is shown as an example in Figure 5. Note that the information indicating the correction table and the reliability information may be stored in a single file written in a markup language or the like, as shown as an example in Figure 5. In this case, either the correction table acquisition unit 820 or the reliability information acquisition unit 821 may acquire the file by reading it from the storage device 12, and the other may acquire the file acquired by the other from the other.

[0054] The correction unit 830 corrects the pixel values ​​of the target scanned image based on the correction table acquired by the correction table acquisition unit 820. As an example, the correction table includes the ideal value R, as shown in Figure 5. i (p), G i (p), and B i The correction method by the correction unit 830 will be explained assuming that each value of (p) is expressed as a numerical value normalized to a value from 0 to 100. First, the correction unit 830 adjusts the RGB color component values ​​of each pixel in the target scanned image (hereinafter referred to as "R s "Gs " and "B s It is written as ". ) obtains. Next, the correction unit 830 obtains R for each pixel. s , G s , and B s Each of these is a multiple R in the correction table. i (p), G i (p), and B i Any two pairs of R from the set of (p) i (p), G i (p), and B i It is determined whether it is located between (p). Next, the correction unit 830 calculates R for each pixel. s , G s , and B s For each of these, two sets of R were identified. i (p), G i (p), and B i The correction is performed using the value obtained by linear interpolation with (p).

[0055] Note that the ideal value is R i (p), G i (p), and B i Since each value in (p) is expressed as a numerical value normalized to a value between 0 and 100, the corrected color component values ​​are also numerical values ​​normalized to a value between 0 and 100. Therefore, for example, if the correction unit 830 outputs each color component value as the corrected pixel value with a predetermined bit width such as 16 bits, the correction unit 830 needs to convert the corrected color component values ​​to the predetermined bit width. For example, if the correction unit 830 outputs each color component value with a 16-bit width, the correction unit 830 performs the conversion using the following equation (4). R c´ = R c / 100 × 65535 G c´ = G c / 100 × 65535 formula (4) B c´ = B c / 100 × 65535 Here, R c , G c , and B cThese are the RGB color component values ​​normalized to values ​​from 0 to 100 after correction. c´ , G c´ , and B c´ This represents the converted RGB color component values, which are obtained by converting the corrected RGB color component values, normalized to values ​​between 0 and 100, to a 16-bit width.

[0056] The output control unit 890 controls the output of information based on reliability information. Information based on reliability information is, for example, information indicating whether the reliability of the correction table is high or low. For example, the output control unit 890 controls the output of information based on reliability information to an output device such as a display device (not shown in Figure 8). For example, if the output device is a display device such as a monitor, the output control unit 890 generates an image based on reliability information, outputs the generated image as an image signal to the display device, and causes the display device to display the image. The display device is not limited to devices that display images such as monitors, but may also be, for example, lamps such as LEDs. Also, the output device is not limited to display devices, but may also be, for example, an audio output device capable of outputting audio signals as sound, such as a speaker or buzzer. In addition to controlling the output of information based on reliability information, the output control unit 890 may also control the output of the corrected target scan image corrected by the correction unit 830. In this case, for example, the output control unit 890 may output the corrected target scan image as an image signal to a display device such as a monitor, and cause the display device to display the corrected target scan image. Alternatively, for example, the output control unit 890 may output the data of the corrected target scan image to the storage device 12 and store the data in the storage device 12.

[0057] The reliability determination unit 840 determines whether the reliability of the correction table indicated by the reliability information is low. If the reliability information expresses the reliability of the correction table as a binary value, for example, the reliability determination unit 840 determines whether the reliability of the correction table indicated by the reliability information is low based on the binary value. Also, if the reliability information expresses the reliability of the correction table as a multi-value or continuous value, for example, the reliability determination unit 840 determines whether the reliability of the correction table is low as follows. In this case, for example, the reliability determination unit 840 determines whether the reliability of the correction table is low by determining whether the value of the multi-value or continuous value is a value that indicates the reliability of the correction table is low. Specifically, for example, if the reliability information expresses the reliability of the correction table as a continuous value, the reliability determination unit 840 determines whether the reliability of the correction table is low by determining whether the continuous value is smaller than a predetermined threshold.

[0058] Furthermore, if the reliability level of the correction table indicated by the reliability information is associated with each color component value, pixel value, or brightness value, the reliability determination unit 840 will determine, for example, whether the reliability of the correction table is low, as follows. In this case, for example, the reliability determination unit 840 will first determine whether the pixel value or brightness value of each pixel in the target scan image corresponds to the pixel value or brightness value associated with low reliability in the reliability information, thereby determining whether the reliability of the correction table is low. Specifically, for example, if the reliability information represents the confidence interval of the correction table by the minimum and maximum brightness values, as shown as an example in Figure 5, the reliability determination unit 840 will determine whether the brightness value of each pixel in the target scan image corresponds to the brightness value of an interval other than the confidence interval. For example, if the brightness values ​​of at least some pixels in the target scan image correspond to the brightness value of an interval other than the confidence interval, the reliability determination unit 840 will determine that the reliability of the correction table is low.

[0059] The output control unit 890 controls the output of information indicating low reliability of the correction table as information based on the reliability information when the reliability determination unit 840 determines that the reliability of the correction table indicated by the reliability information is low. The output control unit 890 may also control the output of information indicating high reliability of the correction table as information based on the reliability information when the reliability determination unit 840 determines that the reliability of the correction table indicated by the reliability information is not low or is high. With the image processing device 800 configured in this way, the reliability of the correction using the correction table can be presented to the user. Furthermore, when the reliability determination unit 840 determines that the reliability of the correction table indicated by the reliability information is low, the output control unit 890 may control the output of information indicating the confidence interval in addition to information indicating low reliability of the correction table. With the image processing device 800 configured in this way, not only can the reliability of the correction using the correction table be presented to the user, but the range of highly reliable or low pixel values ​​or brightness values ​​can also be presented to the user.

[0060] Furthermore, if the reliability information includes information indicating that the reliability of the correction table decreases as it moves further away from the confidence interval, the output control unit 890 may, for example, output information indicating the low reliability of the correction table as follows. In this case, first, the output control unit 890 calculates the difference between the minimum pixel value or brightness value of all pixels in the target scan image and the minimum value of the confidence interval, or the difference between the maximum pixel value or brightness value and the maximum value of the confidence interval. Next, based on the reliability information, the output control unit 890 calculates the degree of low reliability of the correction table corresponding to the magnitude of the calculated difference. Next, the output control unit 890 outputs information indicating the calculated degree of low reliability of the correction table. In this case, the output control unit 890 may output information indicating this by changing the manner in which it outputs according to the calculated degree of low reliability of the correction table. With the image processing device 800 configured in this way, it is possible not only to inform the user that the reliability of the correction using the correction table is low, but also to inform the user of the degree of low reliability of the correction.

[0061] The evaluation area acquisition unit 850 acquires the evaluation area in the target scan image. The evaluation area acquisition unit 850 may acquire the evaluation area by reading information indicating the evaluation area from the storage device 12 or the like, or by extracting information indicating the evaluation area from information provided by a user. Here, a user operation is, for example, an operation to specify a part of the image area of ​​the target scan image. If the image processing device 800 is equipped with the evaluation area acquisition unit 850, the reliability determination unit 840 may determine whether the pixel value or brightness value of each pixel in the evaluation area of ​​the target scan image corresponds to a pixel value or brightness value associated with low reliability in the reliability information.

[0062] When the object to be read is a patch document, for example, the evaluation area acquisition unit 850 acquires an area 320 corresponding to each patch image, as shown as an example in Figure 3, as the evaluation area. In this case, the reliability determination unit 840 may determine whether the reliability of the correction table is low or not, as follows. For example, first, the reliability determination unit 840 calculates statistical values ​​such as the mean, median, or mode of each RGB color component value of all pixels included in the area 320 for each patch image, and acquires the calculated statistical values ​​as the pixel values ​​of each patch image. Next, the reliability determination unit 840 determines whether the acquired pixel values ​​fall within the range of pixel values ​​associated with low reliability in the reliability information. By having the reliability determination unit 840 acquire statistical values ​​of each RGB color component value of multiple pixels included in each patch image as pixel values, the effects caused by reading errors or noise that occur during the reading of the patch image can be suppressed. The reliability determination unit 840 may also calculate a luminance value based on the statistical values ​​of each RGB color component value of multiple pixels included in each patch image, and determine whether the calculated luminance value falls within the range of luminance values ​​associated with low reliability in the reliability information. In this way, the reliability determination unit 840 obtains a luminance value calculated based on the statistical values ​​of the RGB color component values ​​of multiple pixels included in each patch image, thereby suppressing the effects caused by reading errors or noise that occur when reading the patch image.

[0063] The evaluation unit 860 performs an image quality evaluation of the corrected target scan image corrected by the correction unit 830. If the image processing device 800 includes an evaluation area acquisition unit 850, the evaluation unit 860 may perform an image quality evaluation only of the evaluation area of ​​the corrected target scan image. Specifically, for example, the evaluation unit 860 performs an image quality evaluation by calculating Graininess as defined in ISO 24790. The calculation method for Graininess as defined in ISO 24790 and the image quality evaluation method using Graininess are publicly known, so their explanation is omitted. Note that the image quality evaluation method in the evaluation unit 860 is not limited to the calculation method for Graininess as defined in ISO 24790. If the image processing device 800 includes an evaluation unit 860, for example, the output control unit 890 controls the output of information indicating the result of the image quality evaluation in addition to information based on reliability information. With the image processing device 800 configured in this way, the reliability of the correction using the correction table and the result of the image quality evaluation can be presented to the user. As a result, the user, who is the evaluator of the image quality, can understand the reliability of the correction applied to the corrected target scan image that has been evaluated by the evaluation unit 860.

[0064] The operation of the image processing device 800 will be explained with reference to Figure 9. In the following explanation, the symbol "S" means step. Figure 9 is a flowchart showing an example of the processing flow of the image processing device 800 according to Embodiment 2. First, at S901, the correction table acquisition unit 820 acquires a correction table, and the reliability information acquisition unit 821 acquires reliability information. Next, at S902, the scan acquisition unit 810 acquires the target scan data. The order of processing at S901 and S902 is arbitrary. Next, at S903, the evaluation area acquisition unit 850 acquires the evaluation area in the target scan image. Next, at S904, the correction unit 830 corrects the pixel values ​​of the target scan image. Next, at S905, the evaluation unit 860 performs an image quality evaluation of the corrected target scan image.

[0065] Next, in S910, the reliability determination unit 840 determines whether the pixel value or brightness value of each pixel in the target scan image is within the range of unreliable pixel values ​​or brightness values. If in S910 it is determined that the pixel value or brightness value of each pixel in the target scan image is within the range of unreliable pixel values ​​or brightness values, the image processing device 800 executes the process in S912. If in S910 it is determined that the pixel value or brightness value of each pixel in the target scan image is not within the range of unreliable pixel values ​​or brightness values, the image processing device 800 executes the process in S911. Specifically, in S912, the output control unit 890 outputs information indicating that the image quality evaluation result, the corrected scan image, and the correction table are unreliable. In S911, the output control unit 890 outputs information indicating that the image quality evaluation result, the corrected scan image, and the correction table are highly reliable. After S911 or S912, the image processing device 800 completes the process shown in the flowchart in Figure 9.

[0066] The image processing device 800 configured as described above can present the user with the reliability of the correction using the correction table. Furthermore, the image processing device 800 can present the user with both the reliability of the correction using the correction table and the results of the image quality evaluation. Since the information outside the confidence interval is output along with the evaluation value, the user, who is the evaluator of the image quality evaluation, can understand the reliability of the correction for the target scanned image after the image quality evaluation has been performed.

[0067] [Other embodiments] This disclosure can also be implemented by supplying a program that implements one or more of the functions of the embodiments described above to a system or device via a network or storage medium, and by having one or more processors in the computer of that system or device read and execute the program. It can also be implemented by a circuit (e.g., an ASIC) that implements one or more functions.

[0068] Within the scope of this disclosure, it is possible to freely combine the embodiments, modify any component of each embodiment, or omit any component in each embodiment. [Explanation of Symbols]

[0069] 10 Scanners 11 Colorimeter 12 Storage device 100 Image Processing Devices 110 Scan acquisition unit 111 Colorimetric acquisition section 120 Input characteristic acquisition unit 130 Correction Table Generation Unit 140 Trust Information Generation Unit 160 Range acquisition unit 170 Approximation function acquisition section 190 Output section

Claims

1. an input characteristic acquisition means for acquiring a brightness input characteristic of a scanner; a reliability information generating means for generating reliability information indicating the reliability of the correction table based on the magnitude of the error occurring between the input brightness characteristic and the ideal brightness characteristic; and The correction table is for correcting pixel values ​​of a scanned image obtained by reading an object with a scanner to pixel values ​​corresponding to the ideal brightness characteristic in a portion where an error occurs between the input brightness characteristic and the ideal brightness characteristic. An image processing device comprising:

2. a scan acquisition means for acquiring patch scan image data obtained by scanning a medium on which a plurality of patch images having different brightness or color components are formed, using a scanner; a colorimetry acquisition means for acquiring data of a colorimetric image obtained by measuring the color of the medium with a colorimeter; and The input characteristic acquisition means acquires the brightness input characteristic of the scanner that reads the medium based on pixel values ​​of each of the plurality of patch images in the patch scan image and colorimetric values ​​of each of the plurality of patch images in the colorimetric image.

2. The image processing device according to claim 1, wherein:

3. the input characteristic acquisition means acquires, as the lightness input characteristic, an approximate input characteristic obtained by approximating, using an approximation function, a relationship between the pixel values ​​in each of the plurality of patch images in the patch scan image or luminance values ​​calculated based on the pixel values, and the luminance values ​​of the colorimetric values ​​in each of the plurality of patch images in the colorimetric image; The reliability information generating means generates the reliability information based on the magnitude of the error between the approximate input characteristic and the ideal lightness characteristic.

3. The image processing device according to claim 2, wherein:

4. The approximate input characteristics acquired by the input characteristic acquisition means are linear approximations of the relationship between pixel values ​​in each of the plurality of patch images in the patch scan image or luminance values ​​calculated based on the pixel values, and luminance values ​​of colorimetric values ​​in each of the plurality of patch images in the colorimetric image, using a linear approximation function.

4. The image processing device according to claim 3, wherein:

5. The input characteristic acquisition means acquires, as the lightness input characteristic, a relationship between a value of a green component in each of the plurality of patch images in the patch scan image and a luminance value of the colorimetric value in each of the plurality of patch images in the colorimetric image.

5. The image processing device according to claim 2, wherein:

6. a range acquisition means for acquiring a range of pixel values ​​in the patch scan image or a range of luminance values ​​calculated based on the pixel values; and When the error is greater than a predetermined threshold, the reliability information generating means generates the reliability information indicating that the reliability of the correction table is low for a range of pixel values ​​that the scanned image can take or a range of luminance values ​​that the scanned image can take that is not included in the range acquired by the range acquiring means.

6. The image processing device according to claim 2, wherein:

7. When the error is equal to or less than the threshold value over the entire range acquired by the range acquisition means, the reliability information generation means generates the reliability information indicating that the reliability of the correction table is high over the entire range of pixel values ​​that the scanned image can take or the entire range of luminance values ​​that the scanned image can take.

7. The image processing device according to claim 6,

8. When the error is greater than a predetermined threshold, the reliability information generating means generates the reliability information indicating that the reliability of the correction table becomes lower as the range of pixel values ​​or luminance values ​​that the scanned image can take becomes greater, for a range that is not included in the range acquired by the range acquiring means, among the range of pixel values ​​or the range of luminance values ​​that the scanned image can take.

8. The image processing device according to claim 6, wherein:

9. a correction table generating means for generating the correction table for correcting pixel values ​​of the scanned image obtained by reading the object with a scanner to pixel values ​​corresponding to the ideal brightness characteristic for a portion where the error occurs between the input brightness characteristic and the ideal brightness characteristic; Having 9. The image processing device according to claim 2, wherein:

10. the input characteristic acquisition means acquires, as the lightness input characteristic, an approximate input characteristic obtained by approximating, by an approximation function, a relationship between the pixel values ​​in each of the plurality of patch images in the patch scan image or luminance values ​​calculated based on the pixel values ​​and the luminance values ​​of the colorimetric values ​​in each of the plurality of patch images in the colorimetric image; The correction table generating means generates the correction table for correcting the portion where the error occurs between the approximate input characteristic, which is the lightness input characteristic, and the ideal lightness characteristic. The image processing device according to claim 9 ,

11. the correction table generating means replaces pixel values ​​in each of the plurality of patch images in the patch scan image with approximate values ​​approximated by the approximation function, and generates the correction table so that the approximate values ​​are corrected to pixel values ​​corresponding to the ideal brightness characteristic. The image processing device according to claim 10,

12. an approximation function acquisition means for acquiring a second approximation function different from the first approximation function, which is the approximation function, and which acquires, by a polynomial, a relationship between pixel values ​​in each of the plurality of patch images in the patch scan image or luminance values ​​calculated based on the pixel values, and luminance values ​​of colorimetric values ​​in each of the plurality of patch images in the colorimetric image; and the correction table generating means replaces pixel values ​​in each of the plurality of patch images in the patch scan image with approximate values ​​approximated by the second approximation function, and generates the correction table so that the approximate values ​​are corrected to pixel values ​​corresponding to the ideal lightness characteristic. The image processing device according to claim 10,

13. a scan acquisition means for acquiring data of a scanned image obtained by scanning an object to be read with a scanner; a correction table acquisition means for acquiring a correction table for correcting pixel values ​​of the scanned image; a reliability information acquisition means for acquiring reliability information indicating the reliability of the correction table; a correction unit that corrects the pixel values ​​of the scanned image of the reading target based on the correction table; an output control means for controlling the output of information based on the reliability information; Having An image processing device comprising:

14. The method further includes a reliability determination unit that determines whether the reliability of the correction table indicated by the reliability information is low, When it is determined that the reliability of the correction table indicated by the reliability information is low, the output control means controls output of information indicating that the reliability of the correction table is low as information based on the reliability information. The image processing device according to claim 13,

15. The reliability of the correction table indicated by the reliability information is associated with a pixel value or a luminance value, The reliability determination means determines whether or not a pixel value in the scanned image acquired by the scan acquisition means or a luminance value calculated based on the pixel value corresponds to a pixel value or a luminance value associated with low reliability in the reliability information, thereby determining whether or not the reliability of the correction table indicated by the reliability information is low. The image processing device according to claim 14,

16. an evaluation area acquisition means for acquiring an evaluation area in the scanned image of the reading target; and The reliability determination means determines whether or not a pixel value in the evaluation area of ​​the scanned image acquired by the scan acquisition means, or a luminance value calculated based on the pixel value, corresponds to a pixel value or a luminance value associated with low reliability in the reliability information. The image processing device according to claim 15,

17. The image processing device further includes an evaluation unit that evaluates the image quality of the scanned image after correction by the correction unit. The output control means controls output of information indicating a result of the image quality evaluation in addition to the information based on the reliability information.

17. The image processing device according to claim 13, wherein:

18. an input characteristic acquisition step of acquiring a brightness input characteristic of the scanner; a reliability information generating step of generating reliability information indicating the reliability of the correction table based on the magnitude of the error occurring between the input brightness characteristic and the ideal brightness characteristic; and The correction table is for correcting pixel values ​​of a scanned image obtained by reading an object with a scanner to pixel values ​​corresponding to the ideal brightness characteristic in a portion where an error occurs between the input brightness characteristic and the ideal brightness characteristic. An image processing method comprising:

19. a scan acquisition step of acquiring data of a scanned image obtained by reading the object to be read using a scanner; a correction table acquisition step of acquiring a correction table for correcting pixel values ​​of the scanned image; a reliability information acquisition step of acquiring reliability information indicating the reliability of the correction table; a correction step of correcting the pixel values ​​of the scanned image of the reading target based on the correction table; an output control step of controlling output of information based on the reliability information; Having An image processing method comprising:

20. A program for causing a computer to operate as each of the means constituting the image processing apparatus according to any one of claims 1 to 17.

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