A rigid endoscope lens imaging system for cleaning, disinfection and inspection

Abstract

A rigid endoscope lens imaging system for cleaning, disinfection and inspection includes an autofocus module, an image enhancement processing module, a defect detection module, an imaging quality assessment module, and a remote monitoring module. The beneficial effects of the invention are as follows: the invention aims to ensure high-quality imaging and strict cleaning and disinfection of endoscope equipment, realize an efficient, safe and reliable endoscope cleaning and disinfection process, and ensure high-quality imaging.

Description

Technical Field

[0001] The invention relates to the fields of image processing and intelligent medical care, and in particular to a rigid endoscope lens imaging system for cleaning, disinfection and inspection. Background Art

[0002] Rigid endoscope is a widely used device in the medical field. It is usually used for endoscopic examination, surgery and minimally invasive treatment. The key advantage of endoscope is that it enters the human body through a tiny incision to achieve direct observation of organs and tissues. This technology has been widely used in the fields of gastroenterology, gynecology and urology. However, with the continuous development of endoscopic technology, the quality of imaging system and the safety of equipment have become an important issue. In traditional endoscopic operation, after the rigid endoscope lens instruments are sent to the disinfection supply center, the existing inspection process is as follows: receiving the lens in the decontamination area → manual / traceability system registration → visual light inspection → registering the lens status → lens disinfection → manual inspection in the packaging area → packaging sterilization → return to the operating room. The imaging quality and the safety of the equipment are often affected by many factors. For example, the imaging quality may be reduced due to wear, contamination or inaccurate focus of the endoscope lens. This reduction in imaging quality will affect the accuracy of clinical diagnosis and thus affect the treatment effect of patients. On the other hand, the safety of the equipment mainly involves the cleaning and disinfection of the endoscope during multiple uses. If the cleaning and disinfection are not thorough, it may lead to infection or other medical risks.

[0003] As an important tool for modern minimally invasive surgical diagnosis and treatment, the rigid endoscope lens is sent to the disinfection supply center for cleaning and disinfection after use in the hospital operating room. After completion, it is returned from the disinfection supply center and must be fully inspected at the disinfection supply center to prevent the risk of lens damage or blur during the operation. The development of the rigid endoscope lens imaging quality inspection system in this disinfection supply center can check whether the lens imaging is normal and whether it affects the use of the operation. In this context, the research purpose of the present invention is to improve the imaging quality of the rigid endoscope imaging system and ensure the safety of the equipment. Specifically, the present invention aims to improve the performance of the endoscope imaging system through automation technology, image processing, machine learning, and remote monitoring to meet the needs of modern medical practice. The imaging quality of the rigid endoscope imaging system mainly depends on the focus and cleanliness of the lens. In traditional endoscope systems, the focus of the lens is usually done manually by the operator, which not only increases the workload, but also easily produces errors. The cleanliness of the lens is related to the cleaning and disinfection process of the endoscope. During the manual cleaning and disinfection process, improper operation may lead to incomplete cleaning and increase the risk of infection. Therefore, an important goal of the present invention is to introduce automation technology to achieve precise adjustment and thorough cleaning of the lens through automatic focusing, cleaning fluid spraying control, and disinfection process control modules. In addition to imaging quality and equipment safety, remote monitoring and diagnosis are also the research focus of the present invention. In the management of medical equipment, real-time monitoring and remote diagnosis are essential to maintaining the normal operation of the equipment. Traditional equipment maintenance usually relies on manual inspection and repair, which is not only time-consuming and labor-intensive, but may also cause delays in some cases. By introducing a remote monitoring module, the present invention hopes to achieve remote monitoring, fault diagnosis, and remote management of the endoscopic imaging system, thereby improving equipment utilization and reducing downtime. Summary of the invention

[0004] In view of the above problems, the present invention aims to provide a rigid endoscope lens imaging system for cleaning, disinfection and inspection.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a rigid endoscope lens imaging system for cleaning, disinfection and inspection, comprising an automatic focusing module, an image enhancement processing module, a defect detection module, an imaging quality assessment module, and a remote monitoring module. The automatic focusing module ensures that the endoscope lens can focus in real time and provide clear imaging. During the cleaning process of the endoscope, the cleaning liquid spraying control module accurately controls the spraying of the cleaning liquid. The disinfection process control module ensures the effectiveness of the disinfection process by optimizing the concentration, temperature and contact time of the disinfectant. The image enhancement processing module improves the quality of endoscopic imaging and improves the contrast and clarity of the image. The defect detection module is used to automatically detect defects on the surface of the endoscope lens to ensure the normal operation of the equipment. The imaging quality assessment module evaluates the quality of the endoscope imaging system and provides improvement suggestions. The remote monitoring module realizes remote monitoring and management of the endoscope imaging system. Communication technology and data transmission technology are used to realize real-time acquisition of remote data and remote control of equipment. Through remote monitoring, operators can perform real-time fault diagnosis and maintenance to improve the utilization rate of equipment.

[0006] Furthermore, the autofocus module ensures that in the rigid endoscope imaging system, the focus of the lens is automatically adjusted to ensure the clarity of the imaging. The rigid endoscope imaging system includes an image sensor and a focus adjustment unit. The image sensor is responsible for acquiring real-time imaging data. After acquiring the image data, the image data is subjected to blur evaluation. The blur degree of the image is determined by edge detection and contrast analysis. The blur degree of the image is determined according to the number of edges and brightness differences in the image. After the blur evaluation, the focus adjustment unit starts working. The focus adjustment unit includes a motor, a stepper motor, a drive mechanism, and a mechanical control system. The focus adjustment unit changes the focal length of the lens to achieve focusing. By receiving the signal of the blur evaluation unit, the optimal position of the lens is determined. The present invention designs an autofocus algorithm to maximize the clarity of the imaging image and find the optimal position of the lens. A set of sizes is defined as Grayscale image of ,in Represents the grayscale value of a pixel in an image. represents the position of the pixel, and the focal length is , for a point At object distance The imaging position is , satisfying the following relationship:

[0007]

[0008] Use the gradient information of the image as a measure of clarity and define the clarity function for:

[0009]

[0010] in, represents the gradient, for Channel 1, for Channel 2, for No. Channel, Channel 1, Channel 2, ... The channel is related to the position of the lens. The lens is equipped with three independent touch sensors, including a touch structure, a pressure feedback unit, an edge CPU, and an alarm mobile unit. The touch structure can effectively avoid damage to the lens and the object to be inspected caused by physical friction and collision between the lens and the object to be inspected. The pressure feedback unit monitors the pressure between the lens and the object to be inspected detected by the touch structure, and transmits the pressure value back to the edge CPU. The edge CPU uses edge computing technology to classify the acquired real-time pressure value by threshold value, and classifies it into three areas: safe area, warning area, and alarm area. The safe area represents that the pressure value is at 60% of the total pressure range and the current lens position is safe. The warning area represents that the pressure value is at 60%-80% of the total pressure range. The edge CPU sends a warning message to the alarm mobile unit, but the lens position can continue to move. The warning area represents that the pressure value exceeds 80%-100% of the total pressure range. The current lens position is unsafe. The edge CPU sends an alarm message to the alarm mobile unit, and the alarm mobile unit cuts off the forward stepping motor, and the lens cannot continue to move forward. for The important decision factors for The important decision factors for An important decision factor for maximizing the clarity metric function , the lens position needs to be adjusted To maximize , define the objective function To maximize the clarity metric function ,have:

[0011]

[0012] Using the chain rule and the definition of the gradient, we get The optimization equation is used to find the optimal lens position through iterative optimization algorithm. , realizing the autofocus function; the mechanical control system drives the actual movement of the lens and ensures the accuracy and stability of the movement process. It adopts a closed-loop control strategy, which can continuously monitor the position of the lens and adjust the movement of the lens according to the feedback from the image sensor. In this way, the focus adjustment unit ensures the accuracy of focus adjustment while maintaining the stability of the system.

[0013] Furthermore, the image enhancement processing module defines the image enhancement function , the input grayscale image Mapping to output enhanced image ,Right now , using histogram equalization, the contrast is enhanced by adjusting the grayscale distribution of the image. The grayscale histogram is , the grayscale histogram of the output image is ,have , use the sharpening filter to enhance the clarity of the image, and define the sharpening filter as , then the output clear image for ,in Represents the convolution operation and defines the maximum image enhancement metric function ,right Find the maximum value and find the optimal image enhancement function ,right Derivation, get , through the chain rule and gradient, we can get The optimization equation is used to find the optimal image enhancement function through iterative optimization algorithm. , to achieve the best effect of image enhancement processing.

[0014] Furthermore, the defect detection module detects defects in the surface of the endoscope lens to ensure the safe and stable operation of the endoscope equipment. The defect detection module obtains image data from the endoscope imaging system. After obtaining the image data, the defect detection module identifies defects in the image. The defects include cracks, scratches, corrosion, and wear. Morphological analysis of the shapes and contours in the image is used to detect anomalies. Feature extraction is provided to extract the texture, edge, and color features of the image, and these features are used to classify and identify defects.

[0015] Furthermore, the imaging quality assessment module assesses the imaging quality. The imaging quality indicators include resolution, contrast, signal-to-noise ratio, and color reproduction. By analyzing these indicators, the module determines whether the imaging effect meets expectations and finds potential problems. The design of the imaging quality assessment module needs to ensure the accuracy of these indicators and provide actionable improvement suggestions. The contrast is calculated by analyzing the brightness histogram of the image, and the signal-to-noise ratio is obtained by measuring the ratio of the noise level in the image to the effective signal. The resolution assessment is usually achieved by analyzing the high-frequency components in the image. The color reproduction provides consideration of the color distribution and color gamut range of the image, as follows:

[0016] Defining evaluation metrics :

[0017]

[0018] in, and Represent two images respectively. represents a counting variable, Represents the total pixel count, For images No. pixels, For images No. pixels, , , is the characteristic channel index of the image, , , is the characteristic channel index and noise floor number of the additive noise function image By minimizing loss to optimize image quality.

[0019] Furthermore, the remote monitoring module plays an important role in the rigid endoscopic imaging system. Its main function is to realize remote monitoring and management of the endoscopic imaging system. Through this module, operators can obtain real-time data, monitor equipment status, perform remote diagnosis, and perform necessary troubleshooting at a remote location. The implementation of this module involves communication technology, data transmission, and security protocols to ensure the stability, safety, and efficiency of the endoscopic system.

[0020] The innovation and beneficial effects of the present invention are as follows: in terms of automation technology, the present invention introduces an autofocus module to solve the limitation of manual focus in traditional endoscopic imaging systems. The autofocus module realizes automatic focus of the endoscopic lens. The key to this innovation is to eliminate the error of manual focus and improve the accuracy and efficiency of imaging. Through automation, operators can focus more on clinical operations without manually adjusting the focus. In addition, the autofocus module can also adjust the focus in real time to ensure that the best imaging quality can be obtained under different environments and operating conditions. In terms of image processing, the present invention introduces an image enhancement processing module to improve the imaging quality. By enhancing the contrast, sharpness and clarity of the image, the image enhancement processing module provides clearer and more accurate imaging results for clinical diagnosis. This improvement not only improves the accuracy of diagnosis, but also reduces the workload of operators. The remote monitoring module provides remote monitoring and management capabilities. The module uses communication technology and data transmission technology to realize remote monitoring of the endoscopic imaging system, improves the utilization rate of the equipment, and reduces the time and cost of equipment maintenance. Through remote monitoring, operators can obtain imaging data in real time and perform remote diagnosis and troubleshooting. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The invention is further illustrated by the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0022] Figure 1 It is a schematic diagram of the structure of the present invention. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] A rigid endoscope lens imaging system for cleaning, disinfection and inspection comprises an autofocus module, an image enhancement processing module, a defect detection module, an imaging quality assessment module and a remote monitoring module. The autofocus module ensures that the endoscope lens can focus in real time and provide clear imaging. The image enhancement processing module improves the quality of endoscope imaging and improves the contrast and clarity of the image. The defect detection module is used to automatically detect defects on the surface of the endoscope lens to ensure the normal operation of the equipment. The imaging quality assessment module assesses the quality of the endoscope imaging system and provides improvement suggestions. The remote monitoring module realizes remote monitoring and management of the endoscope imaging system, utilizes communication technology and data transmission technology to realize real-time acquisition of remote data and remote control of equipment. Through remote monitoring, operators can perform real-time fault diagnosis and maintenance to improve the utilization rate of equipment.

[0025] Specifically, the automatic focus module ensures that the focus of the lens is automatically adjusted in the rigid endoscope imaging system to ensure the clarity of the imaging. The rigid endoscope imaging system includes an image sensor and a focus adjustment unit. The image sensor is responsible for acquiring real-time imaging data. After acquiring the image data, the image data is subjected to blur evaluation. The blur degree of the image is determined by edge detection and contrast analysis. The blur degree of the image is determined according to the number of edges and brightness difference of the image. After the blur evaluation, the focus adjustment unit starts working. The focus adjustment unit includes a motor, a stepper motor, a drive mechanism, and a mechanical control system. The focus adjustment unit changes the focal length of the lens to achieve focusing. By receiving the signal of the blur evaluation unit, the optimal position of the lens is determined. The present invention designs an automatic focus algorithm to maximize the clarity of the imaging image and find the optimal position of the lens. A set of sizes is defined. Grayscale image of ,in Represents the grayscale value of a pixel in an image. represents the position of the pixel, and the focal length is , for a point At object distance The imaging position is , satisfying the following relationship:

[0026]

[0027] Use the gradient information of the image as a measure of clarity and define the clarity function for:

[0028]

[0029] in, represents the gradient, for Channel 1, for Channel 2, for No. Channel, Channel 1, Channel 2, ... The channel is related to the position of the lens. The lens is equipped with three independent touch sensors, including a touch structure, a pressure feedback unit, an edge CPU, and an alarm mobile unit. The touch structure can effectively avoid damage to the lens and the object to be inspected caused by physical friction and collision between the lens and the object to be inspected. The pressure feedback unit monitors the pressure between the lens and the object to be inspected detected by the touch structure, and transmits the pressure value back to the edge CPU. The edge CPU uses edge computing technology to classify the acquired real-time pressure value by threshold value, and classifies it into three areas: safe area, warning area, and alarm area. The safe area represents that the pressure value is at 60% of the total pressure range and the current lens position is safe. The warning area represents that the pressure value is at 60%-80% of the total pressure range. The edge CPU sends a warning message to the alarm mobile unit, but the lens position can continue to move. The warning area represents that the pressure value exceeds 80%-100% of the total pressure range. The current lens position is unsafe. The edge CPU sends an alarm message to the alarm mobile unit, and the alarm mobile unit cuts off the forward stepping motor, and the lens cannot continue to move forward. for The important decision factors for The important decision factors for An important decision factor for maximizing the clarity metric function , the lens position needs to be adjusted To maximize , define the objective function To maximize the clarity metric function ,have:

[0030]

[0031] Using the chain rule and the definition of the gradient, we get The optimization equation is used to find the optimal lens position through iterative optimization algorithm. , realizing the autofocus function; the mechanical control system drives the actual movement of the lens and ensures the accuracy and stability of the movement process. It adopts a closed-loop control strategy, which can continuously monitor the position of the lens and adjust the movement of the lens according to the feedback from the image sensor. In this way, the focus adjustment unit ensures the accuracy of focus adjustment while maintaining the stability of the system.

[0032] Specifically, the image enhancement processing module defines the image enhancement function , the input grayscale image Mapping to output enhanced image ,Right now , using histogram equalization, the contrast is enhanced by adjusting the grayscale distribution of the image. The grayscale histogram is , the grayscale histogram of the output image is ,have , use the sharpening filter to enhance the clarity of the image, and define the sharpening filter as , then the output clear image for ,in Represents the convolution operation and defines the maximum image enhancement metric function ,right Find the maximum value and find the optimal image enhancement function ,right Derivation, get , through the chain rule and gradient, we can get The optimization equation is used to find the optimal image enhancement function through iterative optimization algorithm. , to achieve the best effect of image enhancement processing.

[0033] Specifically, the defect detection module detects defects in the surface of the endoscope lens to ensure the safe and stable operation of the endoscope equipment. The defect detection module obtains image data from the endoscope imaging system. After obtaining the image data, the defect detection module identifies defects in the image, which include cracks, scratches, corrosion, and wear. Morphological analysis of the shape and contour in the image is used to detect anomalies, and feature extraction is provided to extract the texture, edge, and color features of the image. These features are used to classify and identify defects.

[0034] Specifically, the imaging quality assessment module assesses the imaging quality. The imaging quality indicators include resolution, contrast, signal-to-noise ratio, and color reproduction. By analyzing these indicators, the module determines whether the imaging effect meets expectations and finds potential problems. The design of the imaging quality assessment module needs to ensure the accuracy of these indicators and provide actionable improvement suggestions. The contrast is calculated by analyzing the brightness histogram of the image, and the signal-to-noise ratio is obtained by measuring the ratio of the noise level in the image to the effective signal. The resolution assessment is usually achieved by analyzing the high-frequency components in the image. The color reproduction provides consideration of the color distribution and color gamut range of the image, as follows:

[0035] Defining evaluation metrics :

[0036]

[0037] in, and Represent two images respectively. represents a counting variable, Represents the total pixel count, For images No. pixels, For images No. pixels, , , is the characteristic channel index of the image, , , is the characteristic channel index and noise floor number of the additive noise function image By minimizing loss to optimize image quality.

[0038] Specifically, the remote monitoring module plays an important role in the rigid endoscope imaging system. Its main function is to realize the remote monitoring and management of the endoscope imaging system. Through this module, the operator can obtain real-time data, monitor the equipment status, perform remote diagnosis, and perform necessary troubleshooting at a remote location. The implementation of this module involves communication technology, data transmission, and security protocols to ensure the stability, safety, and efficiency of the endoscope system.

[0039] The innovations and beneficial effects of the present invention: In terms of automation technology, the present invention introduces an autofocus module to solve the limitations of manual focus in traditional endoscopic imaging systems. The autofocus module realizes automatic focus of the endoscopic lens. The key to this innovation is to eliminate the error of manual focus and improve the accuracy and efficiency of imaging. Through automation, operators can focus more on clinical operations without manually adjusting the focus. In addition, the autofocus module can also adjust the focus in real time to ensure that the best imaging quality can be obtained under different environments and operating conditions. In terms of cleaning and disinfection, the present invention solves the safety hazards when the endoscopic equipment is reused through a cleaning liquid spraying control module and a disinfection process control module, and realizes uniform spraying of the cleaning liquid on the lens surface. This innovation ensures the effectiveness of the endoscopic equipment during the cleaning process and avoids the risk of infection caused by incomplete cleaning. The disinfection process control module ensures the safety of the endoscopic equipment during the disinfection process. The two modules work together to ensure that the cleaning and disinfection of the endoscopic equipment meet the safety standards of the medical industry and reduce the risk of infection for patients. In terms of image processing, the present invention introduces an image enhancement processing module to improve the imaging quality. By enhancing the contrast, sharpness and clarity of the image, the image enhancement processing module provides clearer and more accurate imaging results for clinical diagnosis. This improvement not only improves the accuracy of diagnosis, but also reduces the workload of operators. The remote monitoring module provides remote monitoring and management capabilities. The module uses communication technology and data transmission technology to realize remote monitoring of the endoscopic imaging system, improves the utilization rate of the equipment, and reduces the time and cost of equipment maintenance. Through remote monitoring, the operator obtains imaging data in real time and performs remote diagnosis and troubleshooting.

[0040] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A rigid endoscope lens imaging system for cleaning, disinfection and inspection, comprising an autofocus module, an image enhancement processing module, a defect detection module, an imaging quality assessment module and a remote monitoring module, wherein the autofocus module ensures that the endoscope lens can focus in real time and provide clear imaging, the image enhancement processing module improves the quality of endoscope imaging and improves the contrast and clarity of the image, the defect detection module is used to automatically detect defects on the surface of the endoscope lens to ensure the normal operation of the equipment, the imaging quality assessment module assesses the quality of the endoscope imaging system and provides improvement suggestions, and the remote monitoring module realizes remote monitoring and management of the endoscope imaging system, and utilizes communication technology and data transmission technology to realize real-time acquisition of remote data and remote control of equipment; The automatic focusing module ensures that the focus of the lens is automatically adjusted in the rigid endoscope imaging system to ensure the clarity of the imaging. The rigid endoscope imaging system includes an image sensor and a focus adjustment unit. The image sensor is responsible for acquiring real-time imaging data. After acquiring the image data, the image data is subjected to blur evaluation. The blur degree of the image is determined by edge detection and contrast analysis. The blur degree of the image is determined according to the number of edges and brightness difference of the image. After the blur evaluation, the focus adjustment unit starts working. The focus adjustment unit includes a motor, a stepper motor, a driving mechanism, and a mechanical control system. The focus adjustment unit changes the focal length of the lens to achieve focusing. By receiving the signal from the blur evaluation unit, the optimal position of the lens is determined, and an automatic focusing algorithm is designed to maximize the clarity of the image and find the optimal position of the lens. Define a set of grayscale images I of size N×N, where I(i,j) represents the grayscale value of the pixel in the image, (i,j) represents the position of the pixel, the focal length is f, and for a point P at an object distance of z, its imaging position is s, satisfying the following relationship: Using the gradient information of the image as the clarity measure, the clarity function Q is defined as: in, represents the gradient, C1 is the first channel of I(i,j), C2 is the second channel of I(i,j), and C q (i,j) is the qth channel of I(i,j). The 1st channel, the 2nd channel, ... the qth channel are related to the lens position. The lens is equipped with three independent touch sensors, including a touch structure, a pressure feedback unit, an edge CPU, and an alarm mobile unit. The touch structure can effectively avoid damage to the lens and the object to be inspected caused by physical friction and collision between the lens and the object to be inspected. The pressure feedback unit monitors the pressure between the lens and the object to be inspected detected by the touch structure, and transmits the pressure value back to the edge CPU. The edge CPU uses edge computing technology to perform threshold classification on the acquired real-time pressure value, and classifies it into three areas: safe area, warning area, and alarm area. The safe area represents that the current lens position is safe. The warning area represents that the edge CPU sends a warning message to the alarm mobile unit, but the lens position can continue to move. The alarm area represents that the current lens position is unsafe. The edge CPU sends an alarm message to the alarm mobile unit, and the alarm mobile unit cuts off the forward stepping motor, so that the lens cannot continue to move forward. W1 is an important decision factor for C1, W2 is an important decision factor for C2, and W q C q The lens position needs to be adjusted to maximize the clarity metric function Q. To maximize Q, define the objective function J(s) as maximizing the clarity metric function Q, we have: Using the chain rule and the definition of the gradient, we get The optimization equation is used to find the optimal lens position through iterative optimization algorithm. Realize the autofocus function; the mechanical control system drives the actual movement of the lens and ensures the accuracy and stability of the movement process. It adopts a closed-loop control strategy, which can continuously monitor the position of the lens and adjust the movement of the lens according to the feedback of the image sensor. In this way, the focus adjustment unit ensures the accuracy of focus adjustment while maintaining the stability of the system; The imaging quality assessment module assesses the imaging quality. The imaging quality indicators include resolution, contrast, signal-to-noise ratio, and color reproduction. By analyzing these indicators, the module determines whether the imaging effect meets expectations and finds potential problems. The design of the imaging quality assessment module needs to ensure the accuracy of these indicators and provide actionable improvement suggestions. The contrast is calculated by analyzing the brightness histogram of the image, the signal-to-noise ratio is obtained by measuring the ratio of the noise level in the image to the effective signal, the resolution is evaluated by analyzing the high-frequency components in the image, and the color reproduction is obtained by considering the color distribution and color gamut range of the image; The details are as follows: Define the evaluation index J(x,y): Among them, x and y represent two images respectively, temp represents the counting variable, Temp N Represents the total pixel count, x temp is the temp pixel of image x, y temp is the temp-th pixel of image y, A, λ, C are the characteristic channel indexes of the image, Λ, Γ is the characteristic channel index of the additive noise function image, is the noise floor number, and the image quality is optimized by minimizing the J loss.

2. A rigid endoscope lens imaging system for cleaning, disinfection and inspection according to claim 1, characterized in that: The image enhancement processing module defines an image enhancement function F, which maps the input grayscale image I to the output enhanced image I f , that is I f =F(I), using histogram equalization, the contrast is enhanced by adjusting the grayscale distribution of the image. Let the grayscale histogram of I be h I , the grayscale histogram of the output image is have Use a sharpening filter to enhance the clarity of the image. Define the sharpening filter as The output clear image I s for Where * represents the convolution operation, defines the maximum image enhancement metric function M(F), finds the maximum value of M(F), finds the optimal image enhancement function F, and takes the derivative of M(F) to obtain Through the chain rule and gradient, the optimization equation about F is obtained. Through the iterative optimization algorithm, the optimal image enhancement function F is found to achieve the best effect of image enhancement processing.

3. A rigid endoscope lens imaging system for cleaning, disinfection and inspection according to claim 1, characterized in that: The defect detection module detects defects in the surface of the endoscope lens to ensure the safe and stable operation of the endoscope equipment. The defect detection module obtains image data from the endoscope imaging system. After obtaining the image data, the defect detection module identifies defects in the image. Defects include cracks, scratches, corrosion, and wear. Morphological analysis of the shape and contour in the image is used to detect anomalies. Feature extraction is provided to extract the texture, edge, and color features of the image, and these features are used to classify and identify defects.

4. A rigid endoscope lens imaging system for cleaning, disinfection and inspection according to claim 1, characterized in that: The remote monitoring module plays an important role in the rigid endoscope imaging system. Its function is to realize the remote monitoring and management of the endoscope imaging system. Through this module, operators can obtain real-time data, monitor equipment status, perform remote diagnosis, and troubleshoot at a remote location.

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