Low-illumination image enhancement method and system based on visual traction plate

Abstract

The invention discloses a low-illumination image enhancement method and system based on a visual traction plate, and the method comprises the steps: enabling the visual traction plate to be in a low-illumination environment, collecting a low-illumination image, and outputting a first image based on the preprocessing of the low-illumination image; outputting a second image according to the enhancement processing of the first image; outputting an optimized image according to the optimization of the second image; defining a power transmission line area based on the optimized image, and determining a power transmission line according to the identification of the power transmission line area; at the moment, the low-illumination image is sequentially subjected to preprocessing, enhancement processing and optimization and is managed and controlled under multiple processing, so that the contrast ratio and definition of the low-illumination image are managed and controlled under multiple dimensions, the image quality of the low-illumination image is guaranteed, the power transmission line is determined based on the low-illumination image, and the accuracy of the power transmission line is improved. The power transmission line is detected according to the visual traction plate, and the state of the power transmission line is defined based on the multiple parameters of the power transmission line.

Description

Technical Field

[0001] The present invention relates to the field of digital visualization technology, and in particular to a low-light image enhancement method and system based on a visualization traction board. Background Art

[0002] With the development of science and technology, in digital visualization applications, it is often difficult to obtain images under low-light conditions. At this time, by using specific algorithms to optimize the visual effects of images, the main goal is to restore images with complete details from low-light conditions. However, the existing technology still has the problem of low image quality of low-light images. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art. The present invention provides a low-light image enhancement method and system based on a visualization traction board. The visualization traction board is in a low-light environment, collects low-light images, and outputs a first image based on the preprocessing of the low-light image; outputs a second image based on the enhancement processing of the first image; outputs an optimized image based on the optimization of the second image; defines a transmission line area based on the optimized image, and determines the transmission line based on the identification of the transmission line area; at this time, the low-light image is preprocessed, enhanced and optimized in sequence, and is managed under multiple processing to manage the contrast and clarity of the low-light image in multiple dimensions, thereby ensuring the image quality of the low-light image, and determining the transmission line based on the low-light image, thereby detecting the transmission line according to the visualization traction board, and defining the state of the transmission line based on multiple parameters of the transmission line.

[0004] In order to solve the above technical problems, an embodiment of the present invention provides a low-light image enhancement method based on a visual traction board, which is applied to a detection scenario of a transmission line based on a visual traction board; the method comprises: The visualization traction board is in a low-light environment, a low-light image is collected, and a first image is output based on pre-processing of the low-light image; Outputting a second image according to the enhancement processing of the first image; An optimized image is outputted based on the optimization of the second image.

[0005] Optionally, a transmission line region is defined based on the optimized image, and the transmission line is determined based on the identification of the transmission line region; The transmission line is detected according to the visual traction board, and the status of the transmission line is defined based on multiple parameters of the transmission line.

[0006] Optionally, the visualization traction board is in a low-light environment, collecting a low-light image, and outputting a first image based on preprocessing of the low-light image, including: The visualization traction board is in a low-light environment, and the camera configured on the visualization traction board is used to shoot the low-light environment and collect low-light images; Freeze low-light images; Preprocess low-light images.

[0007] Optionally, the visualization traction board is in a low-light environment, a low-light image is collected, and a first image is output based on preprocessing of the low-light image, further comprising: In the preprocessing of low-light images, freeze-frame noise removal and brightness adjustment are performed; defining a processing order of a noise removal process and a brightness adjustment process based on a low-light image; A noise removal process and a brightness adjustment process of the low-light image are triggered along a processing sequence to output a first image.

[0008] Optionally, outputting the second image according to the enhancement processing of the first image includes: Freeze the first image; local contrast enhancement processing based on the first image matching correspondence; triggering enhancement of contrast of the first image according to the local contrast enhancement process; The enhanced first image is subjected to a histogram equalization process to output a second image.

[0009] Optionally, outputting an optimized image according to the optimization of the second image includes: Freeze the second image; determining image noise regions based on the traversal of the second image; Define image noise factors based on image noise regions; Based on the optimization of the image noise factor, a noise-optimized second image is output, and a synchronous deblurring process is performed on the noise-optimized second image to output an optimized image.

[0010] Optionally, defining a power transmission line area based on the optimized image, and determining the power transmission line according to identification of the power transmission line area, includes: Freeze the optimized image; defining circuit segments based on the optimized image; Determine the transmission line area based on the circuit segments.

[0011] Optionally, the defining of the transmission line area based on the optimized image and determining the transmission line according to the identification of the transmission line area further includes: The transmission line is determined based on the identification of the transmission line area.

[0012] Optionally, detecting the transmission line according to the visual traction board and defining the state of the transmission line based on multiple parameters of the transmission line includes: Detect the transmission line based on the visual traction board and trigger the online detection of the transmission line; In the online detection of the transmission line, multiple parameters of the transmission line are collected; the multiple parameters include real-time angle status and tension value.

[0013] Optionally, the detecting the transmission line according to the visual traction board and defining the state of the transmission line based on multiple parameters of the transmission line further includes: constructing a parameter set according to multiple parameters of the transmission line; The state of the transmission line is defined based on a set of parameters.

[0014] Optionally, a low-light image enhancement system based on a visual traction board, comprising: A collection module, used for visualizing the traction board in a low-light environment, collecting a low-light image, and outputting a first image based on preprocessing of the low-light image; An enhancement module, configured to output a second image according to the enhancement processing of the first image; An optimization module, configured to output an optimized image according to the optimization of the second image; an identification module, for defining a transmission line area based on the optimized image, and determining the transmission line according to the identification of the transmission line area; A state module is used to detect the transmission line according to the visual traction board and define the state of the transmission line based on multiple parameters of the transmission line.

[0015] Optionally, the visualization traction board is in a low-light environment, collecting a low-light image, and outputting a first image based on preprocessing of the low-light image, including: The visualization traction board is in a low-light environment, and the camera configured on the visualization traction board is used to shoot the low-light environment and collect low-light images; Preprocess low-light images.

[0016] Optionally, the visualization traction board is in a low-light environment, a low-light image is collected, and a first image is output based on preprocessing of the low-light image, further comprising: In the pre-processing of the low-light image, a noise removal process and a brightness adjustment process of the low-light image are triggered along a processing sequence to output a first image.

[0017] Optionally, outputting the second image according to the enhancement processing of the first image includes: Freeze the first image; Increasing the contrast of the image based on the first image by using an algorithm based on local contrast enhancement; The enhanced first image is subjected to histogram equalization processing to enhance the details of the image, so as to output a second image.

[0018] Optionally, outputting an optimized image according to the optimization of the second image includes: Freeze the second image; determining image noise regions based on the traversal of the second image; Define image noise factors based on image noise regions; Based on the optimization of the image noise factor, a noise-optimized second image is output, and a synchronous deblurring process is performed on the noise-optimized second image to output an optimized image.

[0019] In an embodiment of the present invention, through the method in the embodiment of the present invention, the visualization traction board is in a low-light environment, collects low-light images, and outputs a first image based on the preprocessing of the low-light image; outputs a second image based on the enhancement processing of the first image; outputs an optimized image based on the optimization of the second image; defines a transmission line area based on the optimized image, and determines the transmission line based on the identification of the transmission line area; at this time, the low-light image is preprocessed, enhanced and optimized in sequence, and is managed under multiple processing to manage the contrast and clarity of the low-light image in multiple dimensions, thereby ensuring the image quality of the low-light image, and determining the transmission line based on the low-light image, thereby detecting the transmission line according to the visualization traction board, and defining the state of the transmission line based on multiple parameters of the transmission line. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 is a flow chart of a low-light image enhancement method based on a visual traction board in an embodiment of the present invention; Figure 2 is a flow chart of S11 in the low-light image enhancement method based on a visual traction board in an embodiment of the present invention; Figure 3 is a flow chart of S12 in the low-light image enhancement method based on a visual traction board in an embodiment of the present invention; Figure 4is a flow chart of S13 in the low-light image enhancement method based on a visual traction board in an embodiment of the present invention; Figure 5 is a flow chart of S14 in the low-light image enhancement method based on a visual traction board in an embodiment of the present invention; Figure 6 is a flow chart of S15 in the low-light image enhancement method based on a visual traction board in an embodiment of the present invention; Figure 7 is a stereoscopic schematic diagram of a visualization traction plate in a low-light image enhancement method based on a visualization traction plate in an embodiment of the present invention; Figure 8 is a partial schematic diagram of a visualization traction plate in a low-light image enhancement method based on a visualization traction plate in an embodiment of the present invention; Fig. 9 Schematic diagram of the structure of a low-light image enhancement system based on a visualization traction board in an embodiment of the present invention; Fig.10 The figure is a hardware diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0022] 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.

[0023] Method Embodiment See also Figures 1 to 8 A low-light image enhancement method based on a visual traction board is applied to a detection scene of a transmission line based on a visual traction board; the low-light image enhancement method based on a visual traction board comprises: Step S11: visualizing the traction board in a low-light environment, collecting a low-light image, and outputting a first image based on preprocessing of the low-light image; Step S12: outputting a second image according to the enhancement processing of the first image; Step S13: outputting an optimized image according to the optimization of the second image.

[0024] In the specific implementation process of the present invention, the following steps may also be included: Step S14: defining a power transmission line area based on the optimized image, and determining the power transmission line according to the identification of the power transmission line area; Step S15: Detect the power transmission line according to the visual traction board, and define the state of the power transmission line based on multiple parameters of the power transmission line.

[0025] In an embodiment of the present invention, through the method in the embodiment of the present invention, the visualization traction board is in a low-light environment, collects low-light images, and outputs a first image based on the preprocessing of the low-light image; outputs a second image based on the enhancement processing of the first image; outputs an optimized image based on the optimization of the second image; defines a transmission line area based on the optimized image, and determines the transmission line based on the identification of the transmission line area; at this time, the low-light image is preprocessed, enhanced and optimized in sequence, and is managed under multiple processing to manage the contrast and clarity of the low-light image in multiple dimensions, thereby ensuring the image quality of the low-light image, and determining the transmission line based on the low-light image, thereby detecting the transmission line according to the visualization traction board, and defining the state of the transmission line based on multiple parameters of the transmission line.

[0026] See also Figure 2 , in step S11, the visualization traction board is in a low-light environment, a low-light image is collected, and a first image is output based on preprocessing of the low-light image; In the specific implementation process of the present invention, the specific steps may be: S111: The visualization traction board is in a low-light environment, and a camera configured on the visualization traction board is used to shoot the low-light environment and collect a low-light image; S112: freeze low-light image; S113: Preprocess the low-light image to output a first image.

[0027] In the embodiment of the present application, noise removal and brightness adjustment preprocessing operations are performed on low-light images, which can make the image clearer and the details more obvious. Brightness adjustment is to adjust the brightness level of the image to reduce noise interference and increase the overall brightness; make the image more in line with the visual habits of the human eye and improve the viewing comfort of the image. In addition, the preprocessing operation can also include steps such as color correction.

[0028] In an embodiment of the present application, the visualization traction board is in a low-light environment, and the camera configured on the visualization traction board is used to photograph the low-light environment and collect low-light images to facilitate control of the low-light images, thereby performing image processing on the low-light images and further identifying the low-light images.

[0029] At this time, the low-light image is frozen; the low-light image is preprocessed, and the preprocessing serves as the first layer of image processing means for the low-light image. Therefore, in the preprocessing of the low-light image, the noise removal processing and the brightness adjustment processing are frozen; the processing order of the noise removal processing and the brightness adjustment processing is defined based on the low-light image; the noise removal processing and the brightness adjustment processing of the low-light image are triggered along the processing order to output the first image, thereby controlling the first graphic, and completing the noise removal processing and the brightness adjustment processing of the low-light image.

[0030] See also Figure 3 , in step S12, outputting a second image according to the enhancement processing of the first image; In the specific implementation process of the present invention, the specific steps may be: S121: freeze the first image; S122: increasing the contrast of the image by using a local contrast enhancement algorithm based on the first image; S123: performing histogram equalization processing on the enhanced first image to enhance the details of the image, so as to output a second image.

[0031] In the embodiment of the present application, an algorithm based on local contrast enhancement is used to increase the contrast of the image, and the details of the image are enhanced by histogram equalization. The algorithm based on local contrast enhancement utilizes the characteristics of the high-frequency part and the low-frequency part of the image.

[0032] See also Figure 4 , in step S13, outputting an optimized image according to the optimization of the second image; In the specific implementation process of the present invention, the specific steps may be: S131: freeze the second image; S132: determining an image noise region based on traversal of the second image; S133: defining an image noise factor according to the image noise region; S134: outputting a noise-optimized second image based on the optimization of the image noise factor, and performing synchronous deblurring processing on the noise-optimized second image to output an optimized image.

[0033] In an embodiment of the present application, the second image is frozen and controlled. At this time, the image noise area is determined based on the traversal of the second image; the image noise factor is defined according to the image noise area, and the image noise factor is frozen to facilitate subsequent optimization processing of the image noise factor.

[0034] Therefore, based on the optimization of the image noise factor, a noise-optimized second image is output, and a synchronous deblurring process is performed on the noise-optimized second image to output an optimized image, thereby ensuring the presentation effect of the optimized image.

[0035] Therefore, in order to solve the problem of obtaining clearly visible images in low-light environments, the visual effects are optimized so that people can better observe and perceive these images.

[0036] Under low-light conditions, images are susceptible to noise, blur, and loss of detail, which reduces image quality and visualization. The Visualization Tractor Board is designed to enhance low-light images by applying specific algorithms to improve image brightness, contrast, clarity, and detail.

[0037] Specifically, the visualization tractor can use various image enhancement algorithms, such as histogram equalization, adaptive filtering, local contrast enhancement, etc., to optimize the visual effects of low-light images. These algorithms can improve the visualization quality of images under low-light conditions by adjusting the grayscale distribution of the image, suppressing noise, and enhancing the edges and details of the image.

[0038] The purpose of inventing the visualization traction board is to enable people working under low-light conditions to better obtain and analyze image information and improve work efficiency and accuracy. It can be applied to various fields, such as security monitoring, medical imaging, night vision technology, etc., to provide people with clear and visible image data and promote the smooth progress of related work. The popularization of digital R&D and design tools, the improvement of the CNC rate of key processes, and the in-depth application of networked, intelligent, and personalized production methods in key areas have provided broad space for the widespread application of visualization traction boards.

[0039] See also Figure 5 , S14: defining a transmission line area based on the optimized image, and determining the transmission line according to the identification of the transmission line area; In the specific implementation process of the present invention, the specific steps may be: S141: freeze the optimized image; S142: defining circuit segments based on the optimized image; S143: Determine a transmission line area according to the circuit segment; S144: Determine the transmission line according to the identification of the transmission line area.

[0040] In an embodiment of the present application, the optimized image is frozen, and circuit segments are defined based on the optimized image, so that the transmission line area is determined according to the circuit segments, and then the transmission line area is controlled so as to determine the transmission line according to the identification of the transmission line area.

[0041] See also Figure 6 , S15: detecting the transmission line according to the visual traction board, and defining the state of the transmission line based on multiple parameters of the transmission line; In the specific implementation process of the present invention, the specific steps may be: S151: Detecting the transmission line according to the visual traction board and triggering online detection of the transmission line; S152: In the online detection of the transmission line, multiple parameters of the transmission line are collected; the multiple parameters include a real-time angle state and a tension value; S153: constructing a parameter set according to multiple parameters of the transmission line; S154: Define the state of the transmission line based on the parameter set.

[0042] In the embodiment of the present application, the low-light image is sequentially pre-processed, enhanced, and optimized, and is controlled under multiple processing to control the contrast and clarity of the low-light image in multiple dimensions, thereby ensuring the image quality of the low-light image, and determining the transmission line based on the low-light image, thereby detecting the transmission line according to the visual traction board, and defining the state of the transmission line based on multiple parameters of the transmission line. .

[0043] At this time, the transmission line is detected according to the visual traction board, and the online detection of the transmission line is triggered; in the online detection of the transmission line, multiple parameters of the transmission line are collected; the multiple parameters include real-time angle status and tension value, so as to be compatible with the consideration of real-time angle status and tension value.

[0044] At the same time, a parameter set is constructed according to multiple parameters of the transmission line; the state of the transmission line is defined based on the parameter set; at this time, the low-light image is preprocessed, enhanced and optimized in sequence, and managed under multiple processing to control the contrast and clarity of the low-light image in multiple dimensions, thereby ensuring the image quality of the low-light image, and determining the transmission line based on the low-light image, thereby detecting the transmission line according to the visualized traction board, and defining the state of the transmission line based on multiple parameters of the transmission line.

[0045] Optionally, the visual traction board involved in the patent also has good real-time performance and stability, and can accurately reflect the real-time status of the transmission line. The angle-position sensor can reflect the real-time angle status of the transmission line, the tension sensor can reflect the real-time tension value of the transmission line, and the bottom of the triangle plate has a certain angle, so that it is better to get on the upper line pulley. It has the ability to detect and handle abnormal situations in a timely manner to ensure the safe operation of the power system.

[0046] See also Figure 7 and Figure 8 As shown, for the visualization traction board, the visualization traction board is compatible with the low-light image enhancement algorithm. At this time, the visualization traction board can be structurally divided into a front cover plate 1, a triangular plate 2, a small pull plate 3, a main body 4, a wire-releasing pulley 5, a camera 6, an angle-position sensor 7, a large pull plate 8, a module cover 9, a battery 10, a battery cover 11, a tension sensor 12, an anti-twist device head end 13, an anti-twist device 14, an anti-twist device tail end 15 and other components.

[0047] The angle-position sensor 7, the communication module, and the battery module are arranged inside the traction board body 4 and are integrated with the traction board to prevent the external antenna from being damaged by collision during the construction process.

[0048] The front and rear camera modules are arranged in the middle of the upper side of the traction board. The front and rear video images of the traction board can be monitored in real time during the line laying process. The Bluetooth antenna, WiFi antenna, 4G antenna, Beidou antenna, Lora antenna, etc. are integrated inside to prevent the external antenna from being damaged by collision during construction.

[0049] The triangle plate 2 is welded to the front end of the main body 4. There are four small pull plates 3, which are symmetrically distributed and welded on both sides of the pull plate main body 4 with the central axis as the symmetry line. The tension sensor 12 is connected to the tail of each small pull plate 3 through an axle pin connector.

[0050] The module cover 9 is fixed to the back of the main body 4 by bolts to protect the camera 6 and the sensor in the groove.

[0051] The battery cover 11 is located above the battery 10 and is connected to the main body 4 via an axis structure to facilitate battery replacement.

[0052] The large pull plate 8 is welded to the lower middle part of the main body 4, and the anti-twist device head end 13 is connected to the tail of the large pull plate 8 through a pin shaft. The anti-twist device head end 13 is connected to the anti-twist device 14 through a pin shaft. The anti-twist device 14 is connected to four sections by a shaft pin, and the last section is connected to the anti-twist device tail end 15 through a pin shaft.

[0053] The laser rangefinder and camera are bolted to the last section of the counterweight. The camera and laser rangefinder can work together to monitor data and obtain the corresponding real-time distance to the ground. The measurement range of the laser rangefinder is generally 3.5~5000 meters, while the camera can be used to capture image information. The accuracy of distance measurement can be improved by identifying feature points in the image; or, by analyzing the signal strength reflected by the laser, the properties of the surface, such as material, color, etc., can be determined.

[0054] At this time, the inclination monitoring device monitors the inclination angle of the traction plate in real time, and reports and adjusts any abnormalities in real time.

[0055] The battery cover is located above the battery and is connected to the main body through an axis structure, which makes it easy to replace the battery. This design makes it convenient for users to replace the battery and prolongs the service life of the device.

[0056] The first end of the traction plate anti-twist device is connected to the anti-twist device through a pin shaft. The four sections of the anti-twist device are all connected by axle pins, and the last section is connected to the tail end of the anti-twist device through a pin shaft. This design can effectively prevent the cable or wire rope from twisting during the traction process, ensuring the safety and stability of the construction.

[0057] The laser rangefinder is installed at the tail of the balance hammer. During the movement, the balance hammer is in a vertical downward position, so the real-time distance to the ground can be accurately measured.

[0058] The triangular plate in the present invention has a certain angle, and performs buffering before the traction plate body and the pulley contact, which can effectively reduce the impact.

[0059] In addition, the main idea is to optimize the image by preprocessing, enhancing and post-processing the low-light image. The specific implementation includes the following aspects: 1. Preprocessing: Preprocessing operations such as noise removal and brightness adjustment are performed on low-light images to make the image clearer and the details more obvious. Brightness adjustment is to adjust the brightness level of the image to reduce noise interference and increase the overall brightness. Make the image more in line with the visual habits of the human eye and improve the viewing comfort of the image. In addition, preprocessing operations also include steps such as color correction.

[0060] 2. Enhancement algorithm: An algorithm based on local contrast enhancement is used to increase the contrast of the image, and histogram equalization is used to enhance the details of the image. The algorithm based on local contrast enhancement utilizes the characteristics of the high-frequency and low-frequency parts of the image.

[0061] 3. Optimization processing: Understand the causes of image noise, deblur and denoise the enhanced image, and use a special denoising algorithm to reduce the noise in the image to further improve the clarity and quality of the image.

[0062] In an embodiment of the present invention, through the method in the embodiment of the present invention, the visualization traction board is in a low-light environment, collects low-light images, and outputs a first image based on the preprocessing of the low-light image; outputs a second image based on the enhancement processing of the first image; outputs an optimized image based on the optimization of the second image; defines a transmission line area based on the optimized image, and determines the transmission line based on the identification of the transmission line area; at this time, the low-light image is preprocessed, enhanced and optimized in sequence, and is managed under multiple processing to manage the contrast and clarity of the low-light image in multiple dimensions, thereby ensuring the image quality of the low-light image, and determining the transmission line based on the low-light image, thereby detecting the transmission line according to the visualization traction board, and defining the state of the transmission line based on multiple parameters of the transmission line.

[0063] System Example See also Fig. 9 , Fig. 9 It is a schematic diagram of the structural composition of a detection system for a power transmission line based on a visual traction board in an embodiment of the present invention.

[0064] like Fig. 9 As shown, a detection system for a transmission line based on a visual traction board, the detection system for a transmission line based on a visual traction board comprises: The acquisition module 21 is used to visualize the traction board in a low-light environment, acquire a low-light image, and output a first image based on preprocessing of the low-light image; An enhancement module 22, configured to output a second image according to the enhancement processing of the first image; An optimization module 23, configured to output an optimized image according to the optimization of the second image; an identification module 24, for defining a transmission line region based on the optimized image, and determining the transmission line according to the identification of the transmission line region; The state module 25 is used to detect the transmission line according to the visual traction board and define the state of the transmission line based on multiple parameters of the transmission line.

[0065] Device Embodiment See also Fig.10 , refer to the following Fig.10 The electronic device 40 according to this embodiment of the present invention will be described. Fig.10 The electronic device 40 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0066] like Fig.10As shown, the electronic device 40 is in the form of a general computing device. The components of the electronic device 40 may include but are not limited to: at least one processing unit 41, at least one storage unit 42, and a bus 43 connecting different system components (including the storage unit 42 and the processing unit 41).

[0067] The storage unit stores program codes, which can be executed by the processing unit 41, so that the processing unit 41 executes the steps according to various exemplary embodiments of the present invention described in the above “Embodiment Method” section of this specification.

[0068] The storage unit 42 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit 421 and / or a cache storage unit 422 , and may further include a read-only storage unit (ROM) 423 .

[0069] The storage unit 42 may also include a program / utility 424 having a set (at least one) of program modules 425, such program modules 425 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0070] Bus 43 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0071] The electronic device 40 may also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable a user to interact with the electronic device 40, and / or any device that enables the electronic device 40 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 44. Furthermore, the electronic device 40 may also communicate with one or more networks (e.g., local area networks, wide area networks, and / or public networks, such as the Internet) via a network adapter 45. Fig. 9 As shown, the network adapter 45 communicates with other modules of the electronic device 40 via the bus 43. It should be understood that although Fig. 9 Not shown, other hardware and / or software modules may be used in conjunction with the electronic device 40, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, tape drives, and data backup planning systems.

[0072] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0073] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0074] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0075] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0076] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A low-light image enhancement method based on a visual traction board, characterized in that: include: The visualization traction board is in a low-light environment, a low-light image is collected, and a first image is output based on pre-processing of the low-light image; Outputting a second image according to the enhancement processing of the first image; An optimized image is outputted based on the optimization of the second image.

2. The low-light image enhancement method based on a visual traction board according to claim 1, characterized in that: The visualization traction board is in a low-light environment, collects a low-light image, and outputs a first image based on preprocessing of the low-light image, including: The visualization traction board is in a low-light environment, and the camera configured on the visualization traction board is used to shoot the low-light environment and collect low-light images; Preprocess low-light images.

3. The low-light image enhancement method based on a visual traction board according to claim 2, characterized in that: The visualization traction board is in a low-light environment, collects a low-light image, and outputs a first image based on preprocessing of the low-light image, further comprising: In the pre-processing of the low-light image, a noise removal process and a brightness adjustment process of the low-light image are triggered along a processing sequence to output a first image.

4. The low-light image enhancement method based on a visual traction board according to claim 1, characterized in that: The step of outputting a second image according to the enhancement processing of the first image comprises: Freeze the first image; Increasing the contrast of the image based on the first image by using an algorithm based on local contrast enhancement; The enhanced first image is subjected to histogram equalization processing to enhance the details of the image, so as to output a second image.

5. The low-light image enhancement method based on a visual traction board according to claim 4, characterized in that: Outputting the optimized image according to the optimization of the second image includes: Freeze the second image; determining image noise regions based on the traversal of the second image; Define image noise factors based on image noise regions; Based on the optimization of the image noise factor, a noise-optimized second image is output, and a synchronous deblurring process is performed on the noise-optimized second image to output an optimized image.

6. A low-light image enhancement system based on a visual traction board, characterized in that: include: A collection module, used for visualizing the traction board in a low-light environment, collecting a low-light image, and outputting a first image based on preprocessing of the low-light image; An enhancement module, configured to output a second image according to the enhancement processing of the first image; The optimization module is used to output an optimized image according to the optimization of the second image.

7. The low-light image enhancement system based on a visualization traction board according to claim 6, characterized in that: The visualization traction board is in a low-light environment, collects a low-light image, and outputs a first image based on preprocessing of the low-light image, including: The visualization traction board is in a low-light environment, and the camera configured on the visualization traction board is used to shoot the low-light environment and collect low-light images; Preprocess low-light images.

8. The low-light image enhancement system based on a visualization traction board according to claim 7, characterized in that: The visualization traction board is in a low-light environment, collects a low-light image, and outputs a first image based on preprocessing of the low-light image, further comprising: In the pre-processing of the low-light image, a noise removal process and a brightness adjustment process of the low-light image are triggered along a processing sequence to output a first image.

9. The low-light image enhancement system based on a visualization traction board according to claim 6, characterized in that: The step of outputting a second image according to the enhancement processing of the first image comprises: Freeze the first image; Increasing the contrast of the image based on the first image by using an algorithm based on local contrast enhancement; The enhanced first image is subjected to histogram equalization processing to enhance the details of the image, so as to output a second image.

10. The low-light image enhancement system based on a visualization traction board according to claim 9, characterized in that: Outputting the optimized image according to the optimization of the second image includes: Freeze the second image; determining image noise regions based on the traversal of the second image; Define image noise factors based on image noise regions; Based on the optimization of the image noise factor, a noise-optimized second image is output, and a synchronous deblurring process is performed on the noise-optimized second image to output an optimized image.

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