JP4629629B2 - Digital camera false color evaluation method, digital camera false color evaluation apparatus, and digital camera false color evaluation program - Google Patents

Description

  The present invention relates to a false color evaluation method for a digital camera, and more particularly to a false color evaluation method for a digital camera that quantitatively evaluates a false color generated in a captured image of a digital camera.

  In recent years, digital cameras have become widespread as image capturing devices. This digital camera is classified into a three-plate type, a single-plate type, and the like depending on the structure of the image sensor.

  In a three-plate digital camera, an image sensor such as a CCD or CMOS is configured by three sensor arrays having sensitivity to three colors of Red (R), Green (G), and Blue. Since there is one Red, Green, and Blue image sensor corresponding to one pixel of the captured image, there is an advantage that an accurate color can be recorded. However, since three sensor arrays are required, there is a problem that the structure of the device is complicated. For this reason, in general-purpose digital cameras that are relatively inexpensive, such as home digital cameras, a single-plate type using a single sensor array has become the mainstream.

Such a single-plate digital camera corresponds to an image sensor of one pixel and one color (R, G, or B). FIG. 14 shows an example of the structure of a single plate sensor array. In the case of a single plate type, when the color to be expressed by a certain pixel is not a color corresponding to the pixel, the value of the nonexistent color is obtained by interpolation using the pixel value of the neighboring element. ing. The method of interpolation calculation is, for example, a method of taking the average value of the pixel values of the nearest neighboring pixels, and by applying the patent applicant to define an imaging simulation process and a reproduction simulation process, and by performing an interpolation calculation, more sharpness A method of generating a high-quality image with high quality has been proposed (Patent Document 1).
JP 2004-153753 A

  However, there is a limit to the interpolation calculation described above, and when an image having a sharp edge is captured, a color blur generally called “false color” may occur. For example, when a digital camera having the sensor array structure shown in FIG. 11 is used to capture a monochrome pattern as shown in FIG. 15A, a false color is generated at the monochrome boundary as shown in FIG. 15B.

  The appearance of such false colors is affected by the arrangement of the elements and the interpolation calculation method, but when evaluating how far false colors have occurred, the captured image is displayed on a monitor or the like. There was no choice but to visually observe and evaluate.

  Therefore, the present invention has been made in view of the above problems, and an object thereof is to provide a false color evaluation method and the like for quantitatively evaluating the false color of an image captured by a digital camera.

  In order to solve the above-mentioned problem, the invention according to claim 1 is a false color evaluation method of a single-plate sensor array type digital camera that determines a pixel value of each image sensor using an RGB color filter. An imaging step of imaging with a digital camera, an acquisition step of acquiring image data captured by the digital camera with a computer, and monochromatic image data (for example, at least any two of R, G, or B by the computer) R and G) are generated based on the image data, and the computer uses the computer to generate pixel values of a plurality of pixels included in the single monochrome image data (for example, R), and to each pixel. The difference image value is calculated from the difference pixel value of each pixel included in the corresponding other monochromatic image data (for example, G). A difference image data generation step of generating data, and a false color evaluation of the digital camera based on an evaluation index determined by the computer based on a distribution of the difference pixel values of pixels constituting the difference image data And a false color evaluation method for a digital camera.

  According to this, the false color evaluation of the digital camera can be quantitatively performed.

  In order to solve the above-mentioned problem, the invention described in claim 2 is the digital camera false color evaluation method according to claim 1, wherein the evaluation index is a standard deviation of the difference pixel value. This is a false color evaluation method for digital cameras.

  According to this, the average amount of false color can be quantitatively evaluated.

  In order to solve the above problem, the invention according to claim 3 is the digital camera false color evaluation method according to claim 1 or 2, wherein the evaluation index is a difference between a maximum value and a minimum value of the difference pixel values. This is a false color evaluation method for a digital camera.

  According to this, the presence or absence of a fatal false color can be confirmed (evaluated).

  In order to solve the above-mentioned problem, the invention described in claim 4 is the digital camera false color evaluation method according to any one of claims 1 to 3, wherein the evaluation index is a histogram based on the difference pixel value. A false color evaluation method for a digital camera, characterized by being based on:

  According to this, it is possible to quantitatively evaluate the average amount of false color, and it is possible to evaluate the bias of the false color between the color components of the generated single-color image data.

  In order to solve the above problem, the invention according to claim 5 is the digital camera false color evaluation method according to any one of claims 1 to 4, wherein the evaluation image includes a plurality of spatial frequency components; A false color evaluation method for a digital camera, which is a black-and-white test chart including a pattern configuration having linear or curved components in a plurality of directions.

  According to this, the false color evaluation of the digital camera can be performed with higher accuracy.

  In order to solve the above problem, the invention described in claim 6 is obtained by the computer in the obtaining step in the false color evaluation method for a digital camera according to any one of claims 1 to 5. A false color evaluation method for a digital camera, comprising an adjustment step of adjusting white balance so that an R value, a G value, and a B value of a white portion of an evaluation image indicated by image data are equal.

  According to this, the false color evaluation of the digital camera can be performed with higher accuracy.

  In order to solve the above-described problem, the invention described in claim 7 is the digital camera false color evaluation method according to any one of claims 1 to 6, wherein in the monochrome image data generation step, R, G, B single color image data is generated, and in the differential image data generation step, R and G differential image data is generated based on the R single color image data and the G single color image data, and the G single color image data and B A differential image data of G and B is generated based on the monochrome image data of B, and a differential image data of B and R is generated based on the monochrome image data of B and the monochrome image data of R This is a false color evaluation method.

  According to this, it is possible to perform quantitative false color evaluation including RGB color deviation.

  According to the present invention, it is possible to quantitatively evaluate a false color of a digital camera.

  DESCRIPTION OF EXEMPLARY EMBODIMENTS Hereinafter, preferred embodiments of the invention will be described with reference to the accompanying drawings. In the present embodiment, a case will be described in which the false color evaluation method of the present invention is applied to a false color evaluation system that evaluates a false color of a captured image captured by a digital camera to be evaluated.

[1. Configuration and function of digital camera false color evaluation system]
FIG. 1 is a system configuration diagram showing the configuration of a false color evaluation system S for a digital camera according to this embodiment.

  The false color evaluation system S includes a digital camera 1 to be evaluated and a computer 2 as a false color evaluation apparatus of the present invention.

  The digital camera 1 uses a single-plate sensor array type digital camera composed of RGB color filters and an image sensor.

  First, the test chart T as an example of the evaluation image of the present invention is imaged with the digital camera 1. Then, the computer 2 acquires image data Di obtained by imaging the test chart T from the digital camera 1, and generates each single-color image data Dm of Red (R), Green (G), and Bleu (B) from the image data Di. Then, the difference image data Dd is generated based on each of the monochrome image data Dm. Then, the computer 2 performs the false color evaluation of the digital camera 1 based on the evaluation index resulting from the variation degree of the difference pixel values (difference pixel value distribution) of the pixels constituting the difference image data Dd.

  The test chart T is preferably composed of a binary pattern of white with a reflectance of 100% and black with a reflectance of 0%. Further, in order to evaluate the false color with high accuracy, the reflectance gradient of the boundary portion between the white portion and the black portion is not a warm gradient as shown in FIG. 2 (A) but a steep gradient as shown in FIG. 2 (B). It is preferable that FIG. 3 shows a pattern configuration example of the test chart T. The test chart T preferably has a pattern configuration including various spatial frequency components as shown in pattern example A, and at least the highest resolution from the highest spatial frequency component higher than the highest resolution of the digital camera 1 to be evaluated. A pattern configuration having a spatial frequency component straddling a lower spatial frequency component is preferable. Furthermore, it is preferable that the pattern configuration includes linear or curved components in various directions, for example, an octagon as shown in Pattern Example B, or a pattern configuration with two quadrangles as shown in Pattern Example C. It is preferable that the angle from the horizon has a linear component of 0 degree, 45 degrees, 90 degrees, and 135 degrees. It is more preferable to use a pattern having as many angle components as possible as shown in Pattern Example D, and a circular pattern as shown in Pattern Example E may be used. An example of a test chart that includes a pattern configuration that satisfies the above requirements is a resolution chart defined by ISO12233: 2000.

  Further, when photographing the test chart T, the lighting is set so that the entire test chart T is illuminated uniformly. As shown in FIG. 1, a method of irradiating two lamps (for example, a strobe) from an oblique 45 degree direction of the test chart T is common.

  At this time, in the image obtained by imaging the test chart T, the pixel value of the white portion of the test chart T does not become the maximum RGB value of the digital camera 1, and the pixel value of the black portion does not become the minimum RGB value. As described above, lighting using a strobe and exposure setting of the digital camera 1 are performed. For example, when RGB is output in 8 bits, since the minimum value is “0” and the maximum value is “255”, the pixel value of the white portion is “245” and the pixel value of the black portion is about “20”. Set. In order to accurately evaluate the false color RGB deviation, it is preferable to adjust the white balance so that the pixel values (R value, G value, B value) of the white portion are as equal as possible.

  Thus, the image data Di of the test chart T captured by the digital camera 1 is taken into the computer 2 and the false color is quantitatively evaluated by the difference image data.

[2. Configuration and function of computer]
FIG. 4 is a block diagram showing the configuration of the computer 2. As shown in the figure, the computer 2 includes a CPU (Central Processing Unit), a working RAM (Random Access Memory), various data and programs (including the false color evaluation program for the digital camera of the present invention) as a computer having an arithmetic function. A control unit 11 composed of a ROM (Read Only Memory) and an oscillation circuit, and the like, a storage unit 12 for storing various image data, etc., when executing various image data generation processing, and for the digital camera 1 An input unit 13 where the operator gives various input instructions, a false color evaluation result, a display unit 14 that displays a captured image of the image data Di actually captured as necessary, and an external device connection for connecting the digital camera 1 The control unit 11, the storage unit 12, the input unit 13, the display unit 14, and the external device connection unit 15 are connected to the bus 1. They are connected to each other through a.

  And the control part 11 produces | generates the control information for controlling each structural member, outputs the said control information to a corresponding structural member via the bus | bath 16, and controls the operation | movement of each said structural member, By executing a false color evaluation program for a digital camera, which will be described later, stored in a ROM or the like, the acquisition means, monochromatic image data generation means, difference image data generation means, evaluation means of the present invention in cooperation with other components And it functions as an adjusting means.

[3. False color evaluation process]
Hereinafter, an example of a specific method of the false color evaluation process in the computer 2 will be described with reference to the drawings. FIG. 5 is a flowchart showing the false color evaluation process. This process is executed based on the control of the control unit 11 and starts when the operator operates the input unit 13 to give an instruction.

  First, the control unit 11 acquires image data Di (step S1). The image data Di of the test chart T may be acquired from the digital camera 1 via the external device connection unit 15, or the image data Di previously captured by the digital camera 1 and stored in the storage unit 12. May be acquired from the storage unit 12. Then, white balance adjustment is performed so that the pixel values (R value, G value, B value) of the white portion of the image of the test chart T captured with respect to the acquired image data Di are equal.

  Next, red (R), green (G), and blue (B) single color image data Dm are generated based on the image data Di (step S2). FIG. 6 shows, from an image captured by the digital camera 1 (image data Di), to monochrome image data Dm (R) related to the R component image, monochrome image data Dm (G) related to the G component image, and B component image. It is explanatory drawing which represented typically a mode that the monochromatic image data Dm (B) which each concerns was produced | generated.

  Subsequently, difference image data Dd is generated based on the monochrome image data Dm (R), Dm (G), and Dm (B) generated in step S2 (step S3). Differences between pixel values of pixels included in the monochrome image data Dm (R) and monochrome image data Dm (G), and pixels of pixels included in the monochrome image data Dm (G) and monochrome image data Dm (B). Three types of difference image data Dd (ΔR−G), Dd based on the difference in values and the difference in pixel values of the pixels included in each of the monochrome image data Dm (B) and the monochrome image data Dm (R). (ΔG−B) and Dd (ΔB−R) can be created.

FIG. 7 is an explanatory diagram schematically showing how the difference image data Dd (ΔR−G) is generated based on the monochrome image data Dm (R) and the monochrome image data Dm (G). As shown in the figure, the pixel value R _{(i, j)} in the coordinate value (j, j) of the pixel constituting the R component image indicated by the monochrome image data Dm (R ₎ and the monochrome image data Dm (G) Based on the pixel value G _{(i, j)} in the coordinate value (j, j) of the pixel constituting the G component image, the coordinate value (j, j) of the difference image (ΔR−G) according to (Equation 1) below. The difference pixel value Δ (RG) _{(i, j)} of the pixel at

Similarly, based on the monochrome image data Dm (G) and Dm (B), the difference pixel value Δ (G (G) of the pixel in the coordinate value (j, j) of the difference image (ΔG−B) according to the following (Equation 2). -B) Based on _{(i, j)} and the monochrome image data Dm (B), Dm (R), the pixel values in the coordinate value (j, j) of the difference image (ΔB-R) according to the following (Equation 3) The difference pixel value Δ (BR) _{(i, j) is obtained} .

Difference pixel value Δ (R−G) _{(i, j)} = R _{(i, j)} −G _{(i, j)} + offset (Expression 1)
Difference pixel value Δ (GB) _{(i, j)} = G _{(i, j)} −B _{(i, j)} + offset (Expression 2)
Difference pixel value Δ (B−R) _{(i, j)} = B _{(i, j)} −R _{(i, j)} + offset (Expression 3)
In the formula, “offset” is a value that can be arbitrarily set so that the difference pixel value does not become negative. For example, in the case of outputting 8 bits for each color of RGB, if “offset” is designated as “128”, the difference pixel value can be prevented from being a negative value.

  Finally, the false color evaluation of the digital camera 1 is performed based on the evaluation index determined based on the distribution of the difference pixel values of the pixels constituting each difference image data Dd (step S4).

  The evaluation index determined due to the distribution of the difference pixel value is, for example, the difference between the maximum value and the minimum value of the difference pixel value of a plurality of pixels included in the difference image data Dd, the standard deviation of the difference pixel value, and the difference This is the shape and width W of the histogram of pixel values.

  FIG. 8 shows ISO 12333: 2000 test chart T captured by a plurality of digital cameras 1 (hereinafter referred to as “digital camera 1a”), digital camera 1b, digital camera 1c, and digital camera 1d to be evaluated. Difference image data Dd (ΔR−G), Dd (ΔG−B), and Dd (ΔB−R) are generated, and the standard deviation of the difference pixel value and the difference between the maximum value and the minimum value of the difference pixel value are used as evaluation indexes. FIG. 8A shows the standard deviation of the difference pixel value based on the difference image data Dd (ΔR−G) and the difference between the maximum value and the minimum value of the difference pixel value, and FIG. 8B shows the difference image. The standard deviation of the difference pixel value based on the data Dd (ΔG−B) and the difference between the maximum value and the minimum value of the difference pixel value, FIG. 8C shows the standard of the difference pixel value based on the difference image data Dd (ΔB−R). Deviation and difference pixel value It shows the difference between the maximum value and the minimum value.

  9A is an example of a histogram of difference pixel values based on each difference image data Dd of the digital camera 1a, and FIG. 9B is a histogram of a difference pixel value based on each difference image data Dd of the digital camera 1b. FIG. 9C is an example of a histogram of difference pixel values based on each difference image data Dd of the digital camera 1c, and FIG. 9D is a difference pixel based on each difference image data Dd of the digital camera 1d. It is an example of a histogram of values.

  Actually, the resolution chart (see FIG. 10) defined by ISO12233: 2000 is taken as a test chart T by four digital cameras 1a to 1d, and the difference image data Dd generated from the taken image data Di is applied. The difference image was displayed on the display unit 14, and the accuracy of the false color evaluation method in the present invention was verified while subjectively observing the occurrence of the false color on the difference image.

  FIG. 11 is an enlarged view of a target portion of the test chart T shown in FIG. 10, specifically, an enlarged view of the upper part (shown by a dotted circle) of the black rhombus pattern of the test chart T shown in FIG. is there.

  FIG. 12 is an enlarged display view of the noted portion of the difference image relating to each of the digital cameras 1a to 1d. Specifically, (A) is the digital camera 1a, (B) is the digital camera 1b, and (C). (D) is an enlarged display view of a target portion of a differential image (ΔG-B) related to differential image data Dd (ΔG-B) obtained by the digital camera 1c and (D), respectively.

  As a result, when an enlarged display of the target portion of the difference image (ΔG−B) displayed on the display unit 14 is observed, a false color is generated at the boundary portion (edge) in all of FIGS. You can see that Although the amount of false color differs depending on each digital camera 1a to 1d, it was found that the digital camera 1a, the digital camera 1b, the digital camera 1c, and the digital camera 1d are in order from the smallest false color generation amount. This order matches the order of the standard deviations of the difference pixel values shown in FIG. Further, the larger the width W (for example, full width at half maximum) of the histogram shown in (ΔG-B) of FIGS. 9A to 9D, the larger the false color generation amount, and the smaller the width W, the more the false color generation amount. It is consistent with the smallness.

  In particular, as a result of observing the difference image (ΔG−B) obtained by the digital camera 1d in FIG. 12D, it can be seen that white appears strongly. This is because a large false color of Green (G) appears, and this result is based on the monochrome image data Dm (G) related to the G component image in the histogram of the digital camera 1d shown in FIG. This coincides with the fact that the histogram shape of the difference image data DdΔ (GB) is biased to the plus side.

  In addition, as a result of observing a captured image (not shown) displayed by the digital camera 1a displayed on the display unit 14, unlike the captured images captured by the other digital cameras 1b to 1d, the generation of false colors was small throughout the entire image. However, although the black and white binary test chart T was captured, yellow and blue were clearly confirmed at some positions in the captured image. As a result, as shown in FIG. 8A, the difference between the maximum value and the minimum value of the difference pixel value based on the difference image data Dd (ΔR−G) of the digital camera 1a is the second among the four digital cameras. Largely, as shown in FIGS. 8B and 8C, the maximum value and the minimum value of the difference pixel value based on the difference image data Dd (ΔG−B) and the difference image data Dd (ΔB−R) of the digital camera 1a. The difference is consistent with the largest of the four digital cameras.

  As verified above, by using (checking) the standard deviation or histogram of the difference pixel value as the evaluation index, the average amount of false color over the entire captured image can be evaluated, and the difference pixel value as the evaluation index By using the difference between the maximum value and the minimum value, it is possible to confirm (evaluate) the presence or absence of a fatal false color that can be clearly confirmed in the captured image.

  In the present embodiment described above, the test chart T is imaged by the digital camera 1 to be evaluated, the captured image is acquired as image data Di inside the computer 2, and R, G, and R based on the image data Di are acquired. B monochrome image data Dm is generated. Then, a difference image is obtained from a difference pixel value between a pixel value of a plurality of pixels included in one monochrome image data Dm and a pixel value of each pixel included in another monochrome image data Dm corresponding to each pixel. Data Dd is generated, and the digital camera 1 is configured to perform false color evaluation based on an evaluation index determined based on a distribution of difference pixel values of pixels constituting the difference image data Dd. According to this, since false color evaluation of the digital camera 1 is performed based on the evaluation index, quantitative false color evaluation can be realized.

  In addition, since the evaluation image captured by the digital camera 1 to be evaluated uses the black-and-white binary test chart T, highly accurate false color evaluation becomes possible. Further, since the test chart T including a pattern configuration having various spatial frequency components as shown in FIG. 3 and a pattern configuration having linear or curved components in various directions as shown in FIG. Color evaluation becomes possible.

  Further, lighting and exposure setting of the digital camera 1 are performed so that the pixel value of the white portion of the test chart T does not become the maximum RGB value and the pixel value of the black portion does not become the minimum RGB value. Since it is configured, false color evaluation can be performed without failure.

  Furthermore, since the white balance is adjusted so that the pixel values (R value, G value, B value) of the white portion are as equal as possible, the false color RGB deviation can be evaluated with high accuracy.

  In the above-described embodiment, the entire captured image data Di by the digital camera is used. For example, as shown in FIG. 13A, a false color test area U excluding the edge of the captured image is defined and the false color test is performed. It is also possible to generate the monochrome image data Dm for the area U and perform the false color evaluation only for the false color test area U. Similarly, as shown in FIG. 13B, only the edge portion of the captured image is extracted as a false color test area U, and single color image data Dm is generated from the pixels included in the false color test area U to generate false color. It can also be configured to perform an evaluation. In this way, it is also possible to evaluate the false color by extracting only the imaging region where the false color of the digital camera is to be evaluated.

  Further, in the above-described embodiment, the difference image data Dd is generated based on all the pixels constituting the monochrome image data Dm (the number of pixels of the monochrome image data Dm and the difference image data Dd is the same). However, the difference image data Dd may be generated based on a part of the monochrome image data Dm, for example, pixels constituting a region excluding the edge of the component image related to the monochrome image data Dm.

  Further, in the above-described embodiment, the RGB single-color image data Dm is obtained and three types of difference image data Di are generated. However, the present invention is not limited to this, and at least one difference image data Dd (for example, In order to generate the difference image data DdΔ (R−G)), it is only necessary to have two monochrome image data Dm (for example, monochrome image data Dm (R) and Dm (G)). Since only the difference image data DdΔ (RG) cannot be compared with the difference image data Δ (GB) and DdΔ (BG) relating to the other color components, R, G, B Although it is not known to the detailed false color bias that the false color tends to occur in any of the three colors, it is possible to compare at least the false color bias between the two colors R and G. Moreover, a threshold value is set in advance for the evaluation index, and if it is equal to or greater than the threshold value, a false color occurrence can be displayed on the display unit 14 to be warned. The threshold value of the evaluation index is defined, for example, for the standard deviation of the difference pixel value, the width W of the histogram of the difference pixel value, and the difference between the maximum value and the minimum value of the difference pixel value.

It is a system configuration figure showing the composition of false color evaluation system S of a digital camera. It is explanatory drawing of the white part of a suitable test chart T, and a black part. 3 is a pattern configuration example of a test chart T. 2 is a block diagram showing a configuration of a computer 2. FIG. It is a flowchart which shows the false color evaluation process by the control part. It is explanatory drawing which expressed typically a mode that the monochrome image data Dm was produced | generated. It is explanatory drawing which expressed a mode that the difference image data Dd was produced | generated typically. This is an example in which the standard deviation of the difference pixel value and the difference between the maximum value and the minimum value of the difference pixel value are obtained. It is an example of the histogram of the difference pixel value based on each difference image data Dd. It is a resolution chart defined by ISO12233: 2000. FIG. 4 is an enlarged view of a target portion of a test chart T. (A) is an enlarged display diagram of the difference image (ΔG-B) obtained by the digital camera 1a, (B) is an enlarged display diagram of the difference image (ΔG-B) obtained by the digital camera 1b, and (C) is FIG. 4D is an enlarged display diagram of the difference image (ΔG−B) obtained by the digital camera 1c, and FIG. 4D is an enlarged display diagram of the difference image (ΔG−B) obtained by the digital camera 1d. It is explanatory drawing at the time of defining the false color test area | region U in a captured image. It is an example of the structure of a single plate type sensor array. It is explanatory drawing of false color generation | occurrence | production.

Explanation of symbols

1 (1a, 1b, 1c, 1d) Digital camera 2 Computer 11 Control unit 12 Storage unit 13 Input unit 14 Display unit 15 External device connection unit 16 Bus S Digital camera false color evaluation system T Test chart Di Image data Dm (Dm) (R), Dm (G), Dm (B)) Monochromatic image data Dd (Dd (ΔR−G), Dd (ΔG−B), Dd (ΔB−R)) Difference image data U False color test area

Claims (15)

In the fake color evaluation method of a single-plate sensor array type digital camera that determines the pixel value of each image sensor using an RGB color filter,
An imaging step of imaging an evaluation image with the digital camera;
An acquisition step of acquiring image data captured by the digital camera by a computer;
A monochrome image data generation step of generating at least any two monochrome image data of R, G or B based on the image data by the computer;
The computer calculates a difference image from a difference pixel value between a pixel value of a plurality of pixels included in one monochrome image data and a pixel value of each pixel included in another monochrome image data corresponding to the pixel. A difference image data generation step for generating data;
An evaluation step of performing false color evaluation of the digital camera based on an evaluation index determined by the computer based on a distribution of the difference pixel values of pixels constituting the difference image data;
A false color evaluation method for a digital camera, comprising: The false color evaluation method for a digital camera according to claim 1,
The false color evaluation method for a digital camera, wherein the evaluation index is a standard deviation of the difference pixel value. The false color evaluation method for a digital camera according to claim 1 or 2,
The digital camera false color evaluation method, wherein the evaluation index is a difference between a maximum value and a minimum value of the difference pixel values. In the digital camera false color evaluation method according to any one of claims 1 to 3,
The method for evaluating a false color of a digital camera, wherein the evaluation index is based on a histogram based on the difference pixel value. In the false color evaluation method of the digital camera according to any one of claims 1 to 4,
The false color evaluation method for a digital camera, wherein the evaluation image is a black-and-white test chart including a pattern configuration including a plurality of spatial frequency components and straight or curved components in a plurality of directions. In the digital camera false color evaluation method according to any one of claims 1 to 5,
And an adjustment step of adjusting white balance so that the R value, G value, and B value of the white portion of the evaluation image indicated by the image data acquired in the acquisition step are equalized by the computer. A false color evaluation method for digital cameras. In the digital camera false color evaluation method according to any one of claims 1 to 6,
In the monochrome image data generation step, monochrome image data for each of R, G, and B is generated,
In the difference image data generation step, R and G difference image data is generated based on the R monochrome image data and the G monochrome image data, and G and B are generated based on the G monochrome image data and the B monochrome image data. A false color evaluation method for a digital camera, comprising: generating difference image data of B, and generating difference image data of B and R based on the monochrome image data of B and the monochrome image data of R. In the false color evaluation device for a single-plate sensor array type digital camera that determines the pixel value of each image sensor using an RGB color filter,
Acquisition means for acquiring image data obtained by imaging an evaluation image by the digital camera;
Monochrome image data generation means for generating at least any two monochrome image data of R, G or B based on the image data;
Difference image data is generated from a difference pixel value between a pixel value of a plurality of pixels included in one monochrome image data and a pixel value of each pixel included in the other monochrome image data corresponding to each pixel. Difference image data generation means;
Evaluation means for performing a false color evaluation of the digital camera based on an evaluation index determined due to a distribution of the difference pixel values of pixels constituting the difference image data;
A false color evaluation apparatus for a digital camera, comprising: The false color evaluation apparatus for a digital camera according to claim 8,
The false color evaluation apparatus for a digital camera, wherein the evaluation index is a standard deviation of the difference pixel value. The false color evaluation device for a digital camera according to claim 8 or 9,
The false color evaluation apparatus for a digital camera, wherein the evaluation index is a difference between a maximum value and a minimum value of the difference pixel value. The false color evaluation device for a digital camera according to any one of claims 8 to 10,
The false color evaluation apparatus for a digital camera, wherein the evaluation index is based on a histogram based on the difference pixel value. The false color evaluation device for a digital camera according to any one of claims 8 to 11,
The false color evaluation apparatus for a digital camera, wherein the evaluation image is a black-and-white test chart including a pattern configuration including a plurality of spatial frequency components and a straight line or curve component in a plurality of directions. The false color evaluation device for a digital camera according to any one of claims 8 to 12,
A false digital camera comprising adjusting means for adjusting white balance so that the R value, G value, and B value of the white portion of the evaluation image indicated by the image data acquired by the acquiring means are equal to each other Color evaluation device. The false color evaluation device for a digital camera according to any one of claims 8 to 13,
The monochrome image data generating means generates monochrome image data for each of R, G, and B,
The difference image data generation means generates R and G difference image data based on the R monochrome image data and the G monochrome image data, and generates G and B based on the G monochrome image data and the B monochrome image data. A false color evaluation apparatus for a digital camera, wherein the difference image data is generated, and the difference image data of B and R is generated based on the monochrome image data of B and the monochrome image data of R.   15. A false color evaluation program for causing a computer to function as the false color evaluation device for a digital camera according to claim 8.