Microscope system, image processing method, and program

Abstract

To provide a technique for performing excellent black balance correction, without being affected by the color component of an observation image.SOLUTION: A microscope system includes a microscope for forming an observation optical image, an imaging apparatus for generating the observation image by imaging the observation optical image, a histogram generation unit for generating a histogram of a pixel value for each color component of the observation image, a correction value determination unit for determining a black balance correction value on the basis of the histogram of the pixel value for each color component, a correction unit for generating a corrected observation image by subtracting the black balance correction value from the pixel value for each color component of each pixel of the observation image, and an output device for outputting the corrected observation image.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The disclosure of this specification relates to a microscope system, an image processing method, and a program. [Background technology]

[0002] Fluorescence observation is one of the observation methods performed using a microscope. Fluorescence observation is an observation method that visualizes specific sites or specific proteins or molecules within a cell using fluorescent dyes or fluorescent proteins.

[0003] In fluorescence observation, the autofluorescence of optical components (e.g., objective lens) included in the microscope may cause fluorescence in the background other than the specimen in the observed image, reducing the contrast between the specimen and the background. Therefore, black balance correction is used to prevent such a reduction in contrast. Black balance correction clarifies the difference in brightness between the specimen and the background by subtracting the brightness of the background (brightness due to the autofluorescence of the optical components) from the observed image, thereby obtaining an observed image with high contrast.

[0004] Patent Document 1 discloses a microscope system that performs black balance correction. The microscope system of Patent Document 1 generates a luminance distribution for an observation image, detects the brightest luminance displacement point as a high luminance displacement point and the darkest luminance displacement point as a low luminance displacement point among the displacement points in the luminance distribution, calculates the difference between the luminance value of the high luminance displacement point and the luminance value of the low luminance displacement point, determines the luminance value of the low luminance displacement point as a correction value according to the difference, performs correction by subtracting the correction value from the luminance value of each pixel that constitutes the observation image based on the determination result, and outputs (for example, displays) the corrected observation image. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2010-098719 A Summary of the Invention [Problem to be solved by the invention]

[0006] In the microscope system of Patent Document 1, a correction value (black balance correction value) is determined based on the luminance distribution (luminance histogram) of the observed image.

[0007] However, in the microscope system of Patent Document 1, for example, when the observed image is a color image (an image in which each pixel has an R value, a G value, and a B value), if luminance information is calculated from the color information and black balance correction is performed, the following problems arise.

[0008] The luminance information (Y value) of each pixel of the observed image is calculated from the color information (R value, G value, B value) of the pixel by the following formula (1), for example. Y=0.299*R+0.587*G+0.114*B (1)

[0009] For example, when the observation target is blue (B) monochromatic fluorescence, the red component (R value) and green component (G value) of each pixel of the observation image are close to 0, so that the luminance information (Y value) of each pixel calculated by the above formula (1) is essentially multiplied by the smallest weighting coefficient (0.114) for the blue component (B value) of the pixel. As a result, the correction value determined based on the luminance histogram becomes small. If black balance correction is performed using such a small correction value, the brightness of the background (brightness due to the autofluorescence of the optical member) cannot be sufficiently subtracted from the observation image, and the decrease in contrast between the specimen and the background in the observation image cannot be sufficiently improved.

[0010] An object according to one aspect of the present invention is to provide a technique for performing good black balance correction without being affected by color components of an observed image. [Means for solving the problem]

[0011] A microscope system according to one aspect of the present invention includes a microscope that forms an observation optical image, an imaging device that captures the observation optical image to generate an observation image, a histogram generation unit that generates a histogram of pixel values ​​for each color component of the observation image, a correction value determination unit that determines a black balance correction value based on the histogram of pixel values ​​for each color component, a correction unit that subtracts the black balance correction value from the pixel value for each color component of each pixel of the observation image to generate a corrected observation image, and an output device that outputs the corrected observation image.

[0012] An image processing method according to one aspect of the present invention includes a process in which a computer executes a process of generating a histogram of pixel values ​​for each color component of an observation image generated by capturing an observation optical image formed by a microscope using an imaging device, determining a black balance correction value based on the histogram of pixel values ​​for each color component, and subtracting the black balance correction value from the pixel value for each color component of each pixel of the observation image to generate a corrected observation image.

[0013] A program according to one aspect of the present invention causes a computer to execute a process of generating a histogram of pixel values ​​for each color component of an observation image generated by capturing an observation optical image formed by a microscope using an imaging device, determining a black balance correction value based on the histogram of pixel values ​​for each color component, and subtracting the black balance correction value from the pixel value for each color component of each pixel of the observation image to generate a corrected observation image. Effect of the Invention

[0014] According to the above-described aspect, it is possible to perform good black balance correction without being affected by the color components of the observed image. [Brief description of the drawings]

[0015] [Figure 1] FIG. 1 is a diagram illustrating an example of a configuration of a microscope system according to an embodiment. [Diagram 2] 11A and 11B are diagrams illustrating an example of a part of a process performed by a correction value determination unit. [Diagram 3]1 is a flowchart illustrating an example of image processing performed by an image processing device. [Figure 4] FIG. 13 is a diagram illustrating an example of the configuration of a microscope system according to a first modified example. [Diagram 5] FIG. 11 is a diagram illustrating an example of the configuration of a microscope system according to Modification 2. [Figure 6] FIG. 13 is a diagram illustrating an example of the configuration of a microscope system according to Modification 3. [Figure 7] FIG. 2 is a diagram illustrating an example of a hardware configuration of a computer. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0017] Fig. 1 is a diagram illustrating a configuration of a microscope system according to an embodiment of the present invention, Fig. 2 is a diagram illustrating an example of a part of a process performed by a correction value determination unit.

[0018] The microscope system 1 illustrated in FIG. 1 includes a microscope 10, an imaging device 20, an image processing device 30, and an output device 40.

[0019] The microscope 10 forms an observation optical image of a specimen. The microscope 10 is a microscope capable of fluorescent observation, and forms an observation optical image during fluorescent observation, for example.

[0020] The imaging device 20 is installed in the microscope 10 and captures an observation optical image formed by the microscope 10 to generate an observation image. The imaging device 20 includes an image sensor such as a CCD (Charge Coupled Device) or a CMOS (Complementary Metal Oxide Semiconductor), and the image sensor has, for example, a Bayer array color filter. The observation image generated by the imaging device 20 may be an image in the Bayer array format, or may be a color image obtained by performing a development process on the image in the Bayer array format. The development process includes a process of converting the image in the Bayer array format into a color image, and includes, for example, a demosaic process, a color process, a gamma correction process, an edge enhancement process, and a noise reduction process.

[0021] The image processing device 30 performs processing for performing black balance correction on the observation image generated by the imaging device 20. The image processing device 30 includes a histogram generating section 31, a correction value determining section 32, and a correcting section 33.

[0022] The histogram generating unit 31 generates a histogram of pixel values ​​for each color component of the observation image generated by the imaging device 20. For example, if the observation image generated by the imaging device 20 is an RGB color image (an image in which each pixel has the color components R, G, and B), three histograms are generated: a histogram of pixel values ​​of the R component, a histogram of pixel values ​​of the G component, and a histogram of pixel values ​​of the B component. Alternatively, if the observation image generated by the imaging device 20 is an image in a Bayer array format, four histograms are generated: a histogram of pixel values ​​of the R component, a histogram of pixel values ​​of the Gr component, a histogram of pixel values ​​of the Gb component, and a histogram of pixel values ​​of the B component.

[0023] Hereinafter, the histogram data generated by the histogram generating unit 31 will be expressed as Hist[c][n]. Here, c represents a color component, and n represents a signal level (pixel value). For example, if the observed image is an RGB color image and the signal level of each color component is expressed in 8 bits, c will be any one of the color components R, G, and B, and n will be any one of the values ​​from 0 to 255. In this case, for example, Hist[R]

[32] represents the number of pixels where the signal level of the R component of the RGB color image is 32.

[0024] The correction value determination unit 32 determines a black balance correction value based on the histogram of pixel values ​​for each color component generated by the histogram generation unit 31. In detail, the correction value determination unit 32 determines the black balance correction value as follows.

[0025] First, the correction value determination unit 32 determines, for each color component, a pixel value at which the cumulative number of pixels from the darkest part of the histogram of pixel values ​​of the color component reaches a threshold value as a black balance correction value candidate. Specifically, the minimum x that satisfies the following formula (2) is obtained for each color component from the histogram data Hist[c][n] of pixel values ​​for each color component and a threshold value Thr.

[0026]

number

[0027] The minimum x that satisfies the above formula (2) is the pixel value at which the number of pixels accumulated from the darkest part of the histogram (the solid part in FIG. 2) reaches the threshold value Thr, as shown in FIG. 2, and this is determined as a candidate for the black balance correction value. Hereinafter, x calculated for each color component using the above formula (2) is represented as x[c], where c represents the color component.

[0028] Next, the correction value determination unit 32 determines the maximum value of the black balance correction value candidates determined for each color component as the black balance correction value. Specifically, the black balance correction value X is determined from x[c] for each color component by the following formula (3) or formula (4). Note that the following formula (3) is used when the observed image is an RGB color image, and the following formula (4) is used when the observed image is an image in the Bayer array format. X=MAX(x[R],x[G],x[B]) (3) X=MAX(x[R],x[Gr],x[Gb],x[B]) (4) Here, MAX() represents a function that returns the maximum value among the arguments.

[0029] The reason why the maximum value among the black balance correction value candidates determined for each color component is determined as the black balance correction value in this manner is to prevent the black balance correction performed by the correction unit 33 on the observed image from being insufficient.

[0030] However, if the determined black balance correction value exceeds the upper correction limit, the correction value determination unit 32 determines the upper correction limit as the black balance correction value. That is, in this case, the black balance correction value is clipped to the upper correction limit. Specifically, the final black balance correction value Eval is determined by the following formula (5). Eval=MIN(EvalMax,X) (5) Here, EvalMax represents the upper correction limit value, and MIN() represents a function that returns the minimum value among the arguments.

[0031] The reason why the black balance correction value is clipped to the upper correction limit value when it exceeds the upper correction limit value in this way is to prevent the black balance correction performed by the correction unit 33 on the observed image from becoming excessive.

[0032] The threshold value Thr and the upper correction limit value may be fixed values, such as values ​​determined in consideration of the appearance of the observed image after black balance correction, or may be dynamically determined depending on the ratio of the specimen to the background in the observed image, switching of the observation method, etc.

[0033] The correction unit 33 performs black balance correction on the observation image generated by the imaging device 20. In detail, the correction unit 33 generates a corrected observation image by subtracting the black balance correction value determined by the correction value determination unit 32 from the pixel value for each color component of each pixel of the observation image. Specifically, the correction image is generated as follows.

[0034] For example, if the observed image is an RGB color image and the pixel values ​​of each pixel in the observed image for each color component are R(x,y), G(x,y), and B(x,y), the pixel values ​​R'(x,y), G'(x,y), and B'(x,y) of each color component of each pixel in the corrected observed image are calculated by the following formula (6). R'(x,y)=R(x,y)-Eval G'(x,y)=G(x,y)-Eval B'(x,y)=B(x,y)-Eval (6) It is to be noted that Eval is the black balance correction value determined by the correction value determination unit 32.

[0035] When pixel values ​​are not negative, the following equation (7) is used instead of the above equation (6), and a process of clipping negative pixel values ​​to 0 is added. R'(x,y)=MAX(0,R(x,y)-Eval) G'(x,y)=MAX(0,G(x,y)-Eval) B'(x,y)=MAX(0,B(x,y)-Eval) (7)

[0036] The above is true when the observed image is an RGB color image, but a corrected observed image can be generated in the same manner when the observed image is an image in the Bayer array format. In this case, the black balance correction value Eval is subtracted from the pixel values ​​for each color component of each pixel in the Bayer array format image (the pixel values ​​of each R pixel, each Gr pixel, each Gb pixel, and each B pixel) (if the pixel values ​​are not negative, the negative pixel values ​​are further clipped to 0) to generate a corrected observed image.

[0037] The output device 40 outputs the corrected observation image generated by the correction unit 33. The output device 40 is a display device such as a liquid crystal display, a printing device, etc. For example, the output device 40, which is a display device, displays the corrected observation image generated by the correction unit 33.

[0038] FIG. 3 is a flowchart illustrating an example of image processing performed by the image processing device.

[0039] 3, when an observation image is input from the imaging device 20 to the image processing device 30, the histogram generating unit 31 generates a histogram of pixel values ​​for each color component of the input observation image (step S101). Note that the input observation image is generated by imaging the imaging device 20 with an observation optical image (for example, an observation optical image during fluorescent observation) formed by the microscope 10. The details of the generation of the histogram by the histogram generating unit 31 are as described above.

[0040] Next, the correction value determination unit 32 determines a black balance correction value based on the histogram of pixel values ​​for each color component generated in step S101 (step S102). The details of the determination of the black balance correction value by the correction value determination unit 32 are also as described above.

[0041] Next, the correction unit 33 subtracts the black balance correction value determined in step S102 from the pixel value of each color component of each pixel of the input observation image to generate a corrected observation image (step S103). The details of the generation of the corrected observation image by the correction unit 33 are also as described above.

[0042] The corrected observation image generated by the correction unit 33 is then output from the image processing device 30 to the output device 40, and is displayed by the output device 40, which is, for example, a display device.

[0043] As described above, according to this embodiment, black balance correction can be performed without calculating luminance information (calculation using the above formula (1)), so that good black balance correction can be performed without being affected by the color components of the observed image. Furthermore, such black balance correction makes it possible to sufficiently subtract background brightness (brightness due to autofluorescence of optical members) from the observed image during fluorescence observation, so that the decrease in contrast between the specimen and the background in the observed image can be sufficiently improved.

[0044] This embodiment can also be configured as the following modified examples. In the modified examples shown below, the same elements are given the same reference numerals, and detailed descriptions thereof will be omitted.

[0045] <Variation 1> Fig. 4 is a diagram illustrating a configuration of a microscope system according to Modification 1. In the microscope system 1 according to Modification 1 illustrated in Fig. 4, the image processing device 30 further includes a developing unit 34 in addition to the components of the microscope system 1 illustrated in Fig. 1.

[0046] In the microscope system 1 according to the first modified example, the observation image generated by the imaging device 20 is an image in the Bayer array format, and therefore the corrected observation image generated by the correction unit 33 is also an image in the Bayer array format.

[0047] The developing unit 34 performs a developing process, including a process of converting an image in a Bayer array format into a color image, on the corrected observation image generated by the correcting unit 33. The developing process includes, for example, a demosaic process, a color process, a gamma correction process, an edge enhancement process, and a noise reduction process.

[0048] In the microscope system 1 according to the first modification, the output device (eg, display device) 40 outputs (eg, displays) the corrected observation image that has been subjected to the development process by the development unit .

[0049] According to the first modification, black balance correction is performed before development processing, so that development processing can be performed on a good observed image after black balance correction.

[0050] <Variation 2> Fig. 5 is a diagram illustrating a configuration of a microscope system according to Modification 2. In the microscope system 1 according to Modification 2 illustrated in Fig. 5, the image processing device 30 further includes an image information reduction unit 35 in addition to the components of the microscope system 1 illustrated in Fig. 1.

[0051] The image information reduction unit 35 reduces the amount of information of the observation image generated by the imaging device 20. The image information reduction unit 35 reduces the amount of information by reducing the observation image using known interpolation processing such as nearest neighbor interpolation or bilinear interpolation. The image information reduction unit 35 may perform anti-aliasing by performing LPF (Low Pass Filter) processing on the observation image before the interpolation processing. This makes it possible to suppress the occurrence of aliasing that may occur due to reduction of the observation image by the interpolation processing. Alternatively, the image information reduction unit 35 may reduce the amount of information by dividing the observation image into a predetermined block size and setting the average value of the pixel values ​​of each color component of the pixels included in each block size as the pixel value of each color component of one pixel.

[0052] According to the second modification, the histogram generating unit 31 and the correction value determining unit 32 process the observed image whose amount of information has been reduced by the image information reducing unit 35, thereby enabling faster processing by the histogram generating unit 31 and the correction value determining unit 32. Note that although the image information reducing unit 35 reduces the amount of information by reducing the observed image, this has little effect on the shape of the histogram generated by the histogram generating unit 31 and therefore does not affect the accuracy of the black balance correction value determined by the correction value determining unit 32.

[0053] The second modification is particularly effective when the size of the observed image is large and the histogram is generated using hardware that performs parallel processing. The hardware that performs parallel processing is, for example, a digital signal processor (DSP) or a single instruction multiple data (SIMD) function of a central processing unit (CPU). In general, the generation of a histogram is not suitable for parallel processing. Therefore, when the histogram of a large-sized observed image is generated using hardware that performs parallel processing, the processing time becomes long and real-time processing may become difficult. In contrast, in the second modification, the histogram is generated for a reduced observed image with a reduced amount of information, so the processing time does not become long and real-time processing does not become difficult.

[0054] <Modification 3> Fig. 6 is a diagram illustrating a configuration of a microscope system according to Modification 3. In the microscope system 1 according to Modification 3 illustrated in Fig. 6, the image processing device 30 further includes a correction value stabilization unit 36 ​​in addition to the components of the microscope system 1 illustrated in Fig. 1.

[0055] In the microscope system 1 according to the third modification, the imaging device 20 captures images (generates observation images) at a predetermined frame rate, and for each frame, the image processing device 30 generates a corrected observation image for the observation image of that frame, and the corrected observation image is displayed by the output device 40, which is a display device.

[0056] The correction value stabilization unit 36 smoothes the black balance correction value determined by the correction value determination unit 32 and stabilizes the black balance correction value in the time direction. The correction value stabilization unit 36 smoothes the black balance correction value, for example, by performing a moving average filter process such as a FIR (Finite Impulse Response) filter process or an IIR (Infinite Impulse Response) filter process.

[0057] Also, in the microscope system 1 according to Modification 3, the correction unit 33 generates a corrected observation image using the black balance correction value smoothed by the correction value stabilization unit 36.

[0058] According to Modification 3, for example, even when the black balance correction value determined by the correction value determination unit 32 fluctuates due to the influence of noise during imaging by the imaging device 20, the black balance correction value can be stabilized by the smoothing by the correction value stabilization unit 36. As a result, in the corrected observation image generated by the correction unit 33 and displayed by the output device 40, fluctuations in brightness accompanying fluctuations in the black balance correction value can be suppressed, so that it is possible to prevent the corrected observation image from being difficult to see due to fluctuations in brightness.

[0059] In Modification 3, the correction value stabilization unit 36 may update the smoothed black balance correction value Eval' to Eval' = Eval when the black balance correction value Eval determined by the correction value determination unit 32 satisfies the following formula (8) with respect to the smoothed black balance correction value Eval'. Eval < Eval' - h or Eval' + h < Eval (8) Here, h may be a fixed value or a value dynamically determined according to the value of Eval'.

[0060] The black balance correction value Eval satisfies the above formula (8) when, for example, the observation area is changed during observation and the contents of the observed image change. Even in such a case, black balance correction can be appropriately performed in accordance with the change.

[0061] Although the first to third modifications have been described above, the present embodiment may be configured as a new modification that combines two or more of the first to third modifications.

[0062] In the microscope system 1 described above, the image processing device 30 may be realized by a computer 100 illustrated in Fig. 7. Fig. 7 is a diagram illustrating an example of a hardware configuration of the computer 100.

[0063] The computer 100 illustrated in FIG. 7 includes a processor 101, a memory 102, a storage device 103, a portable storage medium drive device 104, a communication interface 105, and an input / output interface 106, each of which is connected to a bus 107 and capable of transmitting and receiving data to and from each other.

[0064] The processor 101 may be, for example, a single processor, a multi-processor, or a multi-core processor. The processor 101 executes programs such as an OS (Operating System) and applications to perform various processes (for example, image processing exemplified in FIG. 3).

[0065] The memory 102 includes a RAM (Random Access Memory) and a ROM (Read Only Memory). The RAM temporarily stores a part of the program executed by the processor 101. The RAM is also used as a working storage area for the processor 101. The ROM stores the program executed by the processor 101 and various data required for executing the program.

[0066] The storage device 103 is a device for storing data, and is a hard disk drive (HDD), a solid state drive (SSD), or the like.

[0067] The portable storage medium drive device 104 drives the portable storage medium 104a, accesses the stored contents, and reads and writes data. The portable storage medium 104a is a memory device, a flexible disk, an optical disk, a magneto-optical disk, etc. The portable storage medium 104a also includes a CD-ROM (Compact Disc Read Only Memory), a DVD (Digital Versatile Disc), a Blu-ray disk, a USB (Universal Serial Bus) memory, an SD card memory, etc.

[0068] The communication interface 105 is connected to a network by wire or wirelessly, and is an interface for communicating with an external device connected to the network.

[0069] The input / output interface 106 is an interface that is connected to external devices (e.g., the imaging device 20, the output device 40, and an input device) and is used to input and output data between the external devices. The input devices include a keyboard, a mouse, a joystick, a touch panel, etc.

[0070] In such a computer 100, the programs executed by the processor 101 and various data required for the execution of the programs may be stored in the storage device 103 or the portable storage medium 104a, not limited to the memory 102. Furthermore, the programs executed by the processor 101 and various data required for the execution of the programs may be stored in the storage device 103 or the portable storage medium 104a via the communication interface 105 from an external device connected to the network.

[0071] Furthermore, computer 100 is not limited to the example shown in FIG. 7, and may be configured to include a plurality of some of the components shown in FIG. 7, or may be configured to omit some of the components.

[0072] Furthermore, the computer 100 may be configured to include hardware such as a microprocessor, a DSP, an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), an FPGA (Field-Programmable Gate Array), etc. For example, the processor 101 may be implemented using at least one of these pieces of hardware.

[0073] When the image processing device 30 is realized by the computer 100 illustrated in FIG. 7, the functions of the histogram generation unit 31, the correction value determination unit 32, the correction unit 33, the development unit 34, the image information reduction unit 35, and the correction value stabilization unit 36 ​​are realized by the processor 101.

[0074] Although the embodiments and modifications of the present invention have been described above, the present invention is not limited to the above-described embodiments and modifications, and various improvements and modifications can be made without departing from the gist of the present invention. [Explanation of symbols]

[0075] 1. Microscope system 10. Microscope 20 Imaging device 30 Image processing device 31 Histogram Generation Unit 32 Correction value determination unit 33 Correction section 34 Image Information Reduction Section 35 Correction value stabilization section 40 Output Device 100 Computers 101 Processor 102 Memory 103 Storage device 104 Portable storage medium drive device 104a Portable storage media 105 Communication Interface 106 Input / Output Interface 107 Bus

Claims

1. a microscope for forming an observation optical image; an imaging device that captures the observation optical image to generate an observation image; a histogram generating unit for generating a histogram of pixel values ​​for each color component of the observed image; a correction value determination unit that determines a black balance correction value based on a histogram of pixel values ​​for each color component; a correction unit that generates a corrected observation image by subtracting the black balance correction value from a pixel value of each color component of each pixel of the observation image; an output device for outputting the corrected observation image; A microscope system comprising:

2. The correction value determination unit determines, for each of the color components, a pixel value at which a cumulative number of pixels from a darkest part of a histogram of pixel values ​​of the color component reaches a threshold value as a black balance correction value candidate.

2. The microscope system according to claim 1.

3. The correction value determination unit determines a maximum value of the black balance correction value candidates determined for each of the color components as the black balance correction value.

3. The microscope system according to claim 2.

4. When the determined black balance correction value exceeds an upper correction limit, the correction value determination unit determines the upper correction limit as the black balance correction value.

4. The microscope system according to claim 3.

5. a developing unit that performs a developing process on the corrected observation image, including a process of converting an image in a Bayer array format into a color image, The output device outputs the corrected observed image that has been subjected to the development process by the development unit.

5. The microscope system according to claim 1, wherein the first and second lenses are arranged in a first direction.

6. An image information reduction unit that reduces an amount of information of the observation image, The histogram generating unit generates a histogram of pixel values ​​for each color component of the observed image whose amount of information has been reduced by the image information reducing unit.

5. The microscope system according to claim 1, wherein the first and second lenses are arranged in a first direction.

7. a correction value stabilization unit that smoothes the black balance correction value, The correction unit generates the corrected observation image by subtracting the black balance correction value smoothed by the correction value stabilization unit from a pixel value for each color component of each pixel of the observation image.

5. The microscope system according to claim 1, wherein the first and second lenses are arranged in a first direction.

8. A histogram of pixel values ​​for each color component of an observation image is generated by capturing an observation optical image formed by a microscope with an imaging device; determining a black balance correction value based on a histogram of pixel values ​​for each color component; A corrected observed image is generated by subtracting the black balance correction value from the pixel value of each pixel of the observed image for each color component. An image processing method, the processing being carried out by a computer.

9. A histogram of pixel values ​​for each color component of an observation image is generated by capturing an observation optical image formed by a microscope with an imaging device; determining a black balance correction value based on a histogram of pixel values ​​for each color component; A corrected observed image is generated by subtracting the black balance correction value from the pixel value of each pixel of the observed image for each color component. A program that causes a computer to execute a process.

Images