Image processing method, device, equipment, medium and product based on image signals with different central wavelengths

Abstract

The present application discloses an image processing method, device, equipment, medium and product based on image signals with different central wavelengths, and relates to the field of image processing technology. The method includes collecting the first image signal, the second image signal and the third image signal obtained by irradiating the target area with illumination light of three central wavelengths increasing in sequence; calculating the spectral information of the target area image according to the three image signals; filtering the spectral information to obtain the target image signal; extracting the pixel area above the first threshold from the difference image of the second and first image signals as the middle blood vessels and mucosa area; extracting the pixel area above the second threshold from the difference image of the third and second image signals as the deep blood vessels and blood accumulation area; and enhancing the brightness of the target image signal of the two extracted areas, and using the target image signal after the brightness enhancement as the G channel of the output image. The present application can reduce the image processing cost of highlighting bleeding points.

Description

Technical Field

[0001] The present application relates to the field of image processing technology, and in particular to an image processing method, device, equipment, medium and product based on image signals with different central wavelengths. Background Art

[0002] In the medical field, for curative resection of superficial gastrointestinal lesions, surgery such as endoscopic submucosal dissection (ESD) is usually used. In this type of surgery, the doctor confirms the location of the relatively thick blood vessels while performing the incision operation to avoid severe bleeding caused by cutting the thick blood vessels with electric knives.

[0003] At present, in the field of image processing, the technologies for highlighting bleeding points mainly include methods based on tissue spectral characteristics and deep learning methods. The method based on tissue spectral characteristics requires the integration of spectral light-emitting devices of multiple bands in the light source, which has the problem of high equipment cost. The deep learning method requires a large amount of sample data as input and needs to be equipped with a powerful data processor, so the equipment cost will increase significantly and it is difficult to implement. Summary of the invention

[0004] The purpose of the present application is to provide an image processing method, device, equipment, medium and product based on image signals with different central wavelengths, which can reduce the image processing cost of highlighting bleeding points.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides an image processing method based on image signals with different central wavelengths, comprising:

[0007] Collecting a first image signal obtained by irradiating a target area with illumination light of a first central wavelength, a second image signal obtained by irradiating the target area with illumination light of a second central wavelength, and a third image signal obtained by irradiating the target area with illumination light of a third central wavelength; wherein the first central wavelength, the second central wavelength, and the central wavelength increase in sequence;

[0008] Using a spectral inversion method, the spectral information of the target area image is calculated according to the first image signal, the second image signal and the third image signal;

[0009] Filtering the spectral information according to the target wavelength to obtain a target image signal;

[0010] Extracting pixel regions above a first threshold from a first difference image as middle-layer blood vessels and mucosa regions; the first difference image is a difference image between the second image signal and the first image signal;

[0011] Extracting pixel regions above a second threshold from the second difference image as deep blood vessels and blood accumulation regions; the second difference image is a difference image between the third image signal and the second image signal;

[0012] The target image signal is brightness-enhanced using the middle-layer blood vessels and mucosal regions as well as the deep-layer blood vessels and blood accumulation regions, and the target image signal after brightness enhancement is used as the G channel of the output image, the second image signal is used as the B channel of the output image, and the third image signal is used as the R channel of the output image.

[0013] Optionally, the target image signal is enhanced in brightness by using the middle-layer blood vessels and mucosal regions and the deep-layer blood vessels and blood accumulation regions, specifically including:

[0014] Calculating the pixel mean of the middle layer blood vessels and mucosal area to obtain a first pixel mean;

[0015] Calculating a pixel mean of the target image signal to obtain a second pixel mean;

[0016] Calculating pixel means of the deep blood vessels and the blood accumulation area to obtain a third pixel mean;

[0017] Using the ratio of the first pixel mean to the second pixel mean as a first gain coefficient, and using the ratio of the third pixel mean to the second pixel mean as a second gain coefficient;

[0018] The first pixel mean and the first gain coefficient are used to obtain a first gain value, the third pixel mean and the second gain coefficient are used to obtain a second gain value, and the first gain value, the second gain value and the target image signal are added to obtain a target image signal after brightness enhancement.

[0019] Optionally, the range of the first central wavelength is 415nm≤λ1≤440nm, the range of the second central wavelength is 530nm≤λ2≤550nm, and the range of the third central wavelength is 620nm≤λ3≤640nm, wherein λ1 is the first central wavelength, λ2 is the second central wavelength, and λ3 is the third central wavelength.

[0020] Optionally, when the first central wavelength is 430 nm, the second central wavelength is 540 nm, and the third central wavelength is 630 nm, the target wavelength is 600 nm.

[0021] In a second aspect, the present application provides an image processing device based on image signals with different central wavelengths, comprising:

[0022] An image signal acquisition module, used to acquire a first image signal obtained by irradiating a target area with illumination light of a first central wavelength, a second image signal obtained by irradiating the target area with illumination light of a second central wavelength, and a third image signal obtained by irradiating the target area with illumination light of a third central wavelength; the first central wavelength, the second central wavelength, and the central wavelength increase in sequence;

[0023] a spectral information determination module, configured to calculate spectral information of the target area image according to the first image signal, the second image signal and the third image signal by using a spectral inversion method;

[0024] A filtering module, used for filtering the spectral information according to a target wavelength to obtain a target image signal;

[0025] a middle-layer blood vessel and mucosa region extraction module, configured to extract pixel regions above a first threshold from a first difference image as middle-layer blood vessel and mucosa regions; the first difference image being a difference image between the second image signal and the first image signal;

[0026] A deep blood vessel and blood pool region extraction module, used to extract pixel regions above a second threshold from a second difference image as deep blood vessels and blood pool regions; the second difference image is a difference image between the third image signal and the second image signal;

[0027] The output image determination module is used to use the middle-layer blood vessels and mucosal areas and the deep-layer blood vessels and blood accumulation areas to enhance the brightness of the target image signal, and use the target image signal after brightness enhancement as the G channel of the output image, the second image signal as the B channel of the output image, and the third image signal as the R channel of the output image.

[0028] Optionally, the image processing device based on image signals with different central wavelengths further comprises: a display connected to the output image determination module, and the display is used to display the output image corresponding to the target area in real time.

[0029] Optionally, the light sources of the three illumination lights with different central wavelengths are LED light sources.

[0030] In a third aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of any one of the above-mentioned image processing methods based on image signals with different central wavelengths.

[0031] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the above-mentioned image processing methods based on image signals with different central wavelengths.

[0032] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of any of the above-mentioned image processing methods based on image signals with different central wavelengths.

[0033] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0034] The present application provides an image processing method, device, equipment, medium and product based on image signals with different central wavelengths. Based on image signals with different central wavelengths, middle-layer blood vessels and mucosal areas as well as deep-layer blood vessels and blood accumulation areas are extracted, and the brightness of the target image signal is enhanced in the middle-layer blood vessels and mucosal areas as well as the deep-layer blood vessels and blood accumulation areas. The target image signal after brightness enhancement is used as the G channel of the output image, the second image signal is used as the B channel of the output image, and the third image signal is used as the R channel of the output image, thereby highlighting the difference in reflection intensity between the G channel and the R channel, thereby highlighting the bleeding points and deep blood vessels. The light source only needs to provide different central wavelengths, so that the lighting light source design is simple and the number of spectral light-emitting devices is small, thereby reducing the image processing cost of highlighting the bleeding points. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0036] Figure 1 A schematic flow chart of an image processing method based on image signals with different central wavelengths provided in one embodiment of the present application;

[0037] Figure 2 A schematic diagram of a data processing flow of an image processing method based on image signals with different central wavelengths provided in one embodiment of the present application;

[0038] Figure 3 A schematic diagram of functional modules of an image processing device based on image signals with different central wavelengths provided in one embodiment of the present application;

[0039] Figure 4 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0041] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0042] The present application provides an image processing method based on image signals with different central wavelengths, such as Figure 1 As shown, the image processing method based on image signals with different central wavelengths includes:

[0043] Step 101: Collect a first image signal obtained by irradiating a target area with illumination light of a first central wavelength, a second image signal obtained by irradiating a target area with illumination light of a second central wavelength, and a third image signal obtained by irradiating a target area with illumination light of a third central wavelength; the first central wavelength, the second central wavelength, and the central wavelength increase in sequence.

[0044] The target area is the area collected by the endoscope, such as the area collected by the endoscope during submucosal dissection.

[0045] Step 102: using a spectral inversion method to calculate spectral information of the target area image according to the first image signal, the second image signal and the third image signal.

[0046] Step 103: Filter the spectral information according to the target wavelength to obtain a target image signal.

[0047] Step 104: extracting pixel regions above a first threshold from the first difference image as middle-layer blood vessels and mucosa regions; the first difference image is a difference image between the second image signal and the first image signal.

[0048] Step 105: extracting pixel regions above a second threshold from the second difference image as deep blood vessels and blood accumulation regions; the second difference image is a difference image between the third image signal and the second image signal.

[0049] Step 106: Use the middle-layer blood vessels and mucosal areas and the deep-layer blood vessels and blood accumulation areas to enhance the brightness of the target image signal, use the enhanced brightness target image signal as the G channel of the output image, use the second image signal as the B channel of the output image, and use the third image signal as the R channel of the output image.

[0050] The present application extracts middle-layer blood vessels and mucosal areas as well as deep-layer blood vessels and blood accumulation areas based on image signals with different central wavelengths, and enhances the brightness of target image signals in the middle-layer blood vessels and mucosal areas as well as deep-layer blood vessels and blood accumulation areas, and uses the target image signal after brightness enhancement as the G channel of the output image, the second image signal as the B channel of the output image, and the third image signal as the R channel of the output image, thereby highlighting the difference in reflection intensity between the G channel and the R channel, thereby highlighting the bleeding points and deep-layer blood vessels, wherein the lighting light source is simple in design and the number of spectral light-emitting devices is small, thereby reducing the image processing cost of highlighting the bleeding points.

[0051] Among them, in step 106, the brightness of the target image signal is enhanced by using the middle-layer blood vessels and mucosal regions and the deep-layer blood vessels and blood accumulation regions, which specifically includes:

[0052] The pixel means of the middle layer blood vessels and mucosal regions are calculated to obtain a first pixel mean.

[0053] Calculate the pixel mean of the target image signal to obtain a second pixel mean.

[0054] The pixel means of the deep blood vessels and the blood accumulation area are calculated to obtain a third pixel mean.

[0055] The ratio of the first pixel mean value to the second pixel mean value is used as a first gain coefficient, and the ratio of the third pixel mean value to the second pixel mean value is used as a second gain coefficient.

[0056] The first pixel mean and the first gain coefficient are used to obtain a first gain value, the third pixel mean and the second gain coefficient are used to obtain a second gain value, and the first gain value, the second gain value and the target image signal are added to obtain a target image signal after brightness enhancement.

[0057] The range of the first center wavelength is 415nm≤λ1≤440nm, the range of the second center wavelength is 530nm≤λ2≤550nm, and the range of the third center wavelength is 620nm≤λ3≤640nm, wherein λ1 is the first center wavelength, λ2 is the second center wavelength, and λ3 is the third center wavelength.

[0058] In an exemplary embodiment, when the first central wavelength is 430 nm, the second central wavelength is 540 nm, and the third central wavelength is 630 nm, the target wavelength is 600 nm. Figure 2 As shown, the first image signal B1 is obtained by irradiating with the illumination light of the first center wavelength of 415nm, the second image signal G1 is obtained by irradiating with the illumination light of the second center wavelength of 540nm, and the third image signal R1 is obtained by irradiating with the illumination light of the third center wavelength of 630nm. In the subtraction part, the first difference image (G1-B1) between the second image signal G1 and the first image signal B1 is calculated, and the second difference image (R1-G1) between the third image signal R1 and the second image signal G1 is calculated. In the spectral inversion part, the spectral information of the image is calculated according to the spectral inversion method based on the first image signal B1, the second image signal G1, and the third image signal R1. In the 600nm calculation part, according to the spectral information calculated by the spectral inversion part, the 600nm target image signal A1 is obtained by filtering according to the spectral inversion method (for example, using a 3×3 digital filter matrix).

[0059] The middle layer extraction unit inputs the first difference image (G1-B1) and extracts pixel areas with differences higher than a first threshold as middle layer blood vessels and mucosa areas. The first threshold is used to extract middle layer blood vessels and mucosa.

[0060] In the deep layer extraction unit, pixel areas with difference values ​​higher than a second threshold are extracted as deep blood vessels and blood pool areas. The second threshold is used to extract deep blood vessels and blood pools. The second threshold is generally different from the first threshold used to extract middle blood vessels.

[0061] In the brightness equalization section, the brightness of the middle-layer blood vessels and mucosa of the target image signal A1 is enhanced according to the middle-layer blood vessels and mucosa areas obtained by the middle-layer extraction section, and the brightness of the deep-layer blood vessels and blood accumulation areas of the target image signal A1 is enhanced according to the deep-layer blood vessels and blood accumulation areas obtained by the deep-layer extraction section.

[0062] In the image output unit, the input second image signal G1 is assigned to the B channel, the image signal G2 output by the brightness equalizer unit (the target image signal after brightness enhancement) is assigned to the G channel, and the input third image signal R1 is assigned to the R channel to obtain the output image.

[0063] The output image corresponding to the target area is displayed in real time through a display.

[0064] The light source outputs narrow-band blue-violet light with a first center wavelength of 415nm and a half-width of 20nm, broadband green light with a second center wavelength of 540nm and a half-width of 96nm, and narrow-band red light with a third center wavelength of 625nm and a half-width of 20nm. The light sources of the three different center wavelengths of illumination light are LED light sources, but all or part of the multiple light sources may be LEDs. Narrow-band blue light with a first center wavelength of 430nm and a half-width of 20nm may be selected.

[0065] Different wavelengths of illumination light have different penetration depths in tissues. Blood vessels have a high absorption rate for green light around 540nm, so green light can only reach the superficial layer; blood vessels have a low absorption rate for red light around 630nm, so red light can reach deep blood vessels, but the intensity of the reflected light is higher; blood vessels have a higher absorption rate for amber light around 600nm than red light, but lower than green light, so amber light can reach deep blood vessels, but the intensity of the reflected light is lower than red light. Therefore, the difference between amber light and red light at 600nm can highlight deep blood vessels.

[0066] At the same time, when the blood is diluted, the absorption rate of amber light and red light by the diluted blood decreases, but because the absorption characteristics of light near 630nm are originally very low, the reflected light intensity of red light is very strong before and after dilution. Before dilution, the absorption characteristics of 600nm amber light are higher than red light, and after dilution, the absorption rate of amber light is significantly reduced. Therefore, the difference in the reflection intensity of amber light and red light before and after blood dilution can highlight the bleeding point.

[0067] The present application obtains spectral information of about 600nm by a spectral inversion method, and can highlight bleeding points and deep blood vessels by the difference between the inverted spectral information of 600nm and the red light spectral information of about 630nm. The image processing method based on image signals of different central wavelengths of the present application can be applied to image processing of endoscopes, thereby highlighting bleeding points in images on endoscope displays.

[0068] This application has the following technical effects.

[0069] (1) Low latency: No need for sequential illumination, and back-end image processing can quickly obtain images that highlight deep blood vessels and bleeding points.

[0070] (2) Simple operation: By switching the imaging mode, the doctor can intuitively see the real-time image highlighting the bleeding point on the monitor.

[0071] (3) Cost-effectiveness: The lighting source is simple in design, the number of spectral light-emitting devices is small, and their availability is high, which reduces costs.

[0072] (4) Wide range of applications: It can be applied to a variety of medical scenarios, including but not limited to examinations and surgeries of the digestive tract, respiratory tract, etc.

[0073] (5) Promote disease diagnosis and treatment: By highlighting deep blood vessels and bleeding points, it helps doctors identify deep blood vessels and quickly locate bleeding sites, thereby guiding more precise treatment and shortening the time to hemostasis and the duration of surgery.

[0074] Based on the same inventive concept, the embodiment of the present application also provides an image processing device based on image signals with different central wavelengths for implementing the image processing method based on image signals with different central wavelengths involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of one or more image processing devices based on image signals with different central wavelengths provided below can refer to the limitations of the image processing method based on image signals with different central wavelengths above, and will not be repeated here.

[0075] In an exemplary embodiment, Figure 3 As shown, an image processing device based on image signals with different central wavelengths is provided, comprising:

[0076] The image signal acquisition module 201 is used to acquire a first image signal obtained by irradiating a target area with illumination light of a first central wavelength, a second image signal obtained by irradiating a target area with illumination light of a second central wavelength, and a third image signal obtained by irradiating a target area with illumination light of a third central wavelength; the first central wavelength, the second central wavelength, and the central wavelength increase in sequence.

[0077] The spectral information determination module 202 is used to calculate the spectral information of the target area image according to the first image signal, the second image signal and the third image signal by using a spectral inversion method.

[0078] The filtering module 203 is used to filter the spectral information according to the target wavelength to obtain a target image signal.

[0079] The middle-layer blood vessel and mucosa region extraction module 204 is used to extract pixel regions above a first threshold from the first difference image as the middle-layer blood vessel and mucosa region; the first difference image is a difference image between the second image signal and the first image signal.

[0080] The deep blood vessel and blood pool area extraction module 205 is used to extract pixel areas above a second threshold from the second difference image as deep blood vessel and blood pool areas; the second difference image is a difference image between the third image signal and the second image signal.

[0081] The output image determination module 206 is used to use the middle-layer blood vessels and mucosal areas and the deep-layer blood vessels and blood accumulation areas to enhance the brightness of the target image signal, and use the target image signal after brightness enhancement as the G channel of the output image, use the second image signal as the B channel of the output image, and use the third image signal as the R channel of the output image.

[0082] The image processing device based on image signals with different central wavelengths further comprises: a display connected to the output image determination module, the display being used to display the output image corresponding to the target area in real time. The image processing device based on image signals with different central wavelengths may be an endoscope.

[0083] The light sources of the three illumination lights with different central wavelengths are LED light sources.

[0084] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store image processing data based on image signals with different central wavelengths. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an image processing method based on image signals with different central wavelengths is implemented.

[0085] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0086] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0087] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0088] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0089] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0090] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0091] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0092] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. An image processing method based on image signals with different central wavelengths, characterized in that: The image processing method based on image signals with different central wavelengths comprises: Collecting a first image signal obtained by irradiating a target area with illumination light of a first central wavelength, a second image signal obtained by irradiating the target area with illumination light of a second central wavelength, and a third image signal obtained by irradiating the target area with illumination light of a third central wavelength; wherein the first central wavelength, the second central wavelength, and the central wavelength increase in sequence; Using a spectral inversion method, the spectral information of the target area image is calculated according to the first image signal, the second image signal and the third image signal; Filtering the spectral information according to the target wavelength to obtain a target image signal; Extracting pixel regions above a first threshold from a first difference image as middle-layer blood vessels and mucosa regions; the first difference image is a difference image between the second image signal and the first image signal; Extracting pixel regions above a second threshold from the second difference image as deep blood vessels and blood accumulation regions; the second difference image is a difference image between the third image signal and the second image signal; Using the middle-layer blood vessels and mucosal regions and the deep-layer blood vessels and blood accumulation regions, the target image signal is brightness-enhanced, and the target image signal after brightness enhancement is used as a G channel of an output image, the second image signal is used as a B channel of the output image, and the third image signal is used as an R channel of the output image; The target image signal is enhanced in brightness by using the middle-layer blood vessels and mucosal region and the deep-layer blood vessels and blood accumulation region, specifically including: Calculating the pixel mean of the middle layer blood vessels and mucosal area to obtain a first pixel mean; Calculating a pixel mean of the target image signal to obtain a second pixel mean; Calculating pixel means of the deep blood vessels and the blood accumulation area to obtain a third pixel mean; Using the ratio of the first pixel mean to the second pixel mean as a first gain coefficient, and using the ratio of the third pixel mean to the second pixel mean as a second gain coefficient; The first pixel mean and the first gain coefficient are used to obtain a first gain value, the third pixel mean and the second gain coefficient are used to obtain a second gain value, and the first gain value, the second gain value and the target image signal are added to obtain a target image signal after brightness enhancement.

2. The image processing method based on image signals with different central wavelengths according to claim 1, characterized in that: The range of the first central wavelength is , the range of the second central wavelength is , the range of the third central wavelength is ,in, is the first central wavelength, is the second central wavelength, is the third central wavelength.

3. The image processing method based on image signals with different central wavelengths according to claim 1, characterized in that: When the first central wavelength is 430 nm, the second central wavelength is 540 nm, and the third central wavelength is 630 nm, the target wavelength is 600 nm.

4. An image processing device based on image signals with different central wavelengths, characterized in that: The image processing device based on image signals with different central wavelengths comprises: An image signal acquisition module, used to acquire a first image signal obtained by irradiating a target area with illumination light of a first central wavelength, a second image signal obtained by irradiating the target area with illumination light of a second central wavelength, and a third image signal obtained by irradiating the target area with illumination light of a third central wavelength; the first central wavelength, the second central wavelength, and the central wavelength increase in sequence; a spectral information determination module, configured to calculate spectral information of the target area image according to the first image signal, the second image signal and the third image signal by using a spectral inversion method; A filtering module, used for filtering the spectral information according to a target wavelength to obtain a target image signal; a middle-layer blood vessel and mucosa region extraction module, configured to extract pixel regions above a first threshold from a first difference image as middle-layer blood vessel and mucosa regions; the first difference image being a difference image between the second image signal and the first image signal; A deep blood vessel and blood pool region extraction module, used to extract pixel regions above a second threshold from a second difference image as deep blood vessels and blood pool regions; the second difference image is a difference image between the third image signal and the second image signal; an output image determination module, configured to enhance the brightness of the target image signal by using the middle-layer blood vessels and mucosal regions and the deep-layer blood vessels and blood accumulation regions, and use the target image signal after the enhancement of brightness as the G channel of the output image, use the second image signal as the B channel of the output image, and use the third image signal as the R channel of the output image; The target image signal is enhanced in brightness by using the middle-layer blood vessels and mucosal region and the deep-layer blood vessels and blood accumulation region, specifically including: Calculating the pixel mean of the middle layer blood vessels and mucosal area to obtain a first pixel mean; Calculating a pixel mean of the target image signal to obtain a second pixel mean; Calculating pixel means of the deep blood vessels and the blood accumulation area to obtain a third pixel mean; Using the ratio of the first pixel mean to the second pixel mean as a first gain coefficient, and using the ratio of the third pixel mean to the second pixel mean as a second gain coefficient; The first pixel mean and the first gain coefficient are used to obtain a first gain value, the third pixel mean and the second gain coefficient are used to obtain a second gain value, and the first gain value, the second gain value and the target image signal are added to obtain a target image signal after brightness enhancement.

5. The image processing device based on image signals with different central wavelengths according to claim 4, characterized in that: The image processing device based on image signals with different central wavelengths further includes: a display connected to the output image determination module, and the display is used to display the output image corresponding to the target area in real time.

6. The image processing device based on image signals with different central wavelengths according to claim 4, characterized in that: The light sources of the three illumination lights with different central wavelengths are LED light sources.

7. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the image processing method based on image signals with different central wavelengths as described in any one of claims 1 to 3.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the image processing method based on image signals with different central wavelengths described in any one of claims 1 to 3 is implemented.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the image processing method based on image signals with different central wavelengths described in any one of claims 1 to 3 is implemented.

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