40results about How to "Clear details" patented technology

The invention discloses a small tandem wing unmanned aerial vehicle folding mechanism which comprises a pair of front wings, a pair of rear wings, a pair of vertical empennages and a fuselage, the front wings and the rear wings are in tandem wing layout on the fuselage after being unfolded, and in a folding state, the pair of front wings rotate backwards around a front rotating shaft to coincide with the back of the fuselage, and the pair of vertical empennages rotate backwards around a rear rotating shaft to coincide with the back of the fuselage. The pair of rear wings rotate forwards around the rear rotating shaft to coincide with the bottom of the fuselage, and the pair of vertical empennages rotate downwards to coincide with the side face of the fuselage. A front spring support is installed on the back of the fuselage and located at the front end of the front rotating shaft, and the pair of front wings is connected with the front spring support through tension springs. A rear spring support is installed at the bottom of the fuselage and located at the rear end of the rear rotating shaft, and the pair of rear wings is connected with the rear spring support through tension springs. The tandem wing layout is adopted, the front wings and the rear wings serve as lift wings, the area of the wings is increased, the size of the unmanned aerial vehicle is reduced, and combat maneuverability is improved.

The invention discloses a pantograph structure abnormity real-time detection method and system, and the method comprises the steps: obtaining a pantograph image in a video stream of a bullet train in real time, and inputting a pantograph target detection model; performing target detection on the pantograph by adopting a target detection algorithm, and if an abnormal state occurs, triggering an alarm; if the abnormal state does not occur, performing picture cutting on the pantograph region bounding box to obtain a pantograph body region image; inputting the pantograph body area image into a pantograph key point detection model; and detecting the structure of the pantograph by adopting a key point detection algorithm, and if the structure is abnormal, triggering an alarm. According to the method and the system, target detection is carried out on the pantograph body and the abnormal state, and a rapid and accurate result is provided for detection and attitude matching of the pantograph key point.

The invention relates to the technical field of biomedical image processing, and provides a frozen electron tomography image denoising method based on self-supervised learning, and the method comprises the following steps: S1, obtaining a tilted series projection image of frozen electron tomography, and carrying out the three-dimensional reconstruction of the tilted series projection image to obtain a noise image V (x); s2, carrying out two-dimensional denoising on the inclined series projection image to obtain a denoised inclined series projection image, and reconstructing the denoised inclined series projection image into a smooth image # imgabs0 # S3, respectively cutting V (x) and # imgabs1 # into a series of overlapped image blocks, and constructing a training data pair for the noise image blocks by using an average volume blind spot replacement strategy; s4, constructing a denoising model combining an anti-artifact pooling layer and a feature focusing attention module; and S5, inputting the training data pair and the corresponding smooth image block into the denoising model for training until the model converges. According to the method, the problems that the denoising effect is too smooth and artifacts exist in the prior art are solved, and the denoised image has the characteristics of high signal-to-noise ratio and clear details.

The invention discloses a photoelectric wafer defect detection method, and belongs to the technical field of semiconductors. The detection method comprises the steps that the surface of a photoelectric wafer is covered with a quantum dot precursor solution, annealing is carried out, after a quantum dot film is formed, irradiation is carried out under ultraviolet light, a displayed fluorescence signal can mark defects on the surface of the photoelectric wafer, and the purpose of detecting the defects of the photoelectric wafer is achieved. The quantum dots used in the invention have excellent fluorescence efficiency and stability, and can provide a high-contrast marking effect in an SEM image. Therefore, the detection of micron-scale and nano-scale defects is more accurate, and the details are clearer. A traditional fluorescence labeling solution is limited in infiltration capacity in nanoscale defects and can only cover the surface. The quantum dots can penetrate into the defect to form a mark with the depth ratio as high as 1: 3. The depth marking capability is helpful for comprehensively knowing the internal structure of the defect and the defect extension condition. In addition, the quantum dots have excellent adaptability and multifunctionality, and show good stability and coupling effect under different types of wafer conditions.

The invention discloses a calibration method of a polarization focal plane imaging system and an imaging system, relates to the field of photoelectric imaging and remote sensing detection imaging, and solves the problems of low correction efficiency and difficulty in correcting a system with a changed polarization state in the conventional polarization error correction technology. According to the calibration method, a plurality of coding patterns and corresponding polarization modulation matrixes are obtained based on the collected uniform light field and serve as calibration results. The polarization error correction method comprises the steps of obtaining an observation intensity vector based on a target scene; a corresponding polarization modulation matrix is obtained based on the coding pattern according to a coding polarization modulation matrix lookup table, and then a down-sampling Stokes vector after polarization error correction is obtained; and completing the correction of the polarization error through an imaging reconstruction method. A polarization focal plane imaging system comprises an imaging lens, a DMD digital micromirror array coding module, a focal plane DoFP polarization detector and an imaging reconstruction module. The method is suitable for the fields of remote sensing detection, target identification, environment monitoring and the like.

The invention provides an unfavorable weather-oriented automatic driving multi-sensor fusion method, relates to the field of unmanned driving assistance in a closed scene, and provides an unmanned vehicle auxiliary sensing system depending on 5G communication, and the auxiliary sensing system comprises an unmanned vehicle, a millimeter wave radar, a camera sensing sensor, a laser radar sensor and a CAN communication system. According to the method, the communication transmission speed is high, the calculated amount is accurate, the obstacle information and distance in front of the autonomous vehicle in adverse weather can be accurately predicted, and efficient and accurate data fusion between the unmanned vehicle and sensor equipment is achieved. According to the invention, stable and efficient operation of the unmanned vehicle can be effectively guaranteed.

The invention belongs to the technical field of polarization image processing, and particularly relates to a color polarization image demosaicing image fusion method based on deep learning, which comprises the following steps: S1, constructing a color polarization image demosaicing convolutional neural network model, and carrying out demosaicing processing on color polarization image data with missing pixel values to obtain a color polarization image demosaicing convolutional neural network model; and generating four panchromatic polarization images with different polarization angles, wherein the convolutional neural network model is composed of two sub-networks, namely a color demosaicing network and a polarization demosaicing network. The method can effectively solve the pixel interpolation problem of CPFA data of an existing color polarization image, improves the definition of the color polarization image, makes up for the technical defects of polarization imaging in a dynamic environment, provides the color polarization image based on the attention mechanism, analyzes the difference of imaging target information expressed by a color intensity image and a color polarization degree image, and improves the image quality. And an attention mechanism module is introduced in a targeted manner, so that the obtained fused image has better quality compared with a traditional fused image.

The invention discloses a frequency modulation and wavelet sub-band guided double-domain collaborative Transformer X-ray image denoising method, which comprises the following steps of: acquiring a noise-containing digital ray original image and a corresponding clear reference image, and constructing a data set after preprocessing the noise-containing digital ray original image and the corresponding clear reference image; constructing a network model of a double-domain collaborative coding-decoding architecture; performing 3 * 3 deep convolution on an input image to extract shallow layer features; in the encoding stage, ETB and AFMB are alternately stacked to represent local and global information, a WB-LKED module is embedded to strengthen fine-grained features, and WDB executes down-sampling and transmits high-frequency features to a decoding end; in the decoding stage, the WUB recovers the resolution through double-path up-sampling, integrates the same-scale features of an encoder, enhances details by using high-frequency features, splices the features, then carries out ETB and AFMB refining, obtains output features through 3 * 3 deep convolution, and combines a global residual error connection optimization result; and training the model by using the data set, inputting a to-be-denoised image, and outputting a final result. According to the method, the problems of weak complex noise interference resistance, poor detail retention effect and limited CNR improvement can be solved.

The invention provides a camouflage target detection method and system based on hierarchical graph interaction and unit clustering, and the method comprises the steps: obtaining a to-be-detected image, converting the to-be-detected image into a set number of feature graph units through unit division and linear transformation, inputting all the feature graph units into a plurality of continuous region sensing unit focusing attention modules, and carrying out the recognition of the region sensing unit focusing attention modules; and removing redundancy based on the similarity of a self-attention mechanism by using a clustering algorithm, performing self-attention mechanism calculation on the screened feature map units, and outputting a first-level feature map. And inputting the first hierarchy feature maps output by the focusing attention modules of the adjacent region sensing units into a hierarchy map interaction self-attention module in pairs, converting the first hierarchy feature maps into map structures, performing hierarchy feature interaction, and projecting the interacted map structures back to the original space to output a second hierarchy feature map. And inputting the second-level feature maps into a confidence aggregation feature fusion decoder, refining an ambiguity region, fusing all the second-level feature maps, and outputting a camouflage target. The detection precision can be improved.

This invention discloses a differential VGA signal decoding and display device, relating to the display field. It includes a signal input module, an ESD protection module, a differential receiving module, a synchronization separation module, an image decoding driver module, a display module, an audio processing module, and a control module. These modules are interconnected and work together to decode, process, and display differential VGA signals. This differential VGA signal decoding and display device solves the problems of short transmission distance, weak anti-interference capability, limited resolution, and high power consumption associated with traditional VGA interfaces. It also achieves full compatibility with traditional VGA devices, integrating audio processing, local playback, intelligent signal enhancement, and remote monitoring and management functions. It achieves reliable conversion from analog to differential signals, supports high-definition display, and has a transmission distance of up to 50 meters, while maintaining full compatibility with traditional VGA devices. This technology is particularly suitable for professional fields such as industrial automation and medical imaging, meeting the diverse display and intelligent operation and maintenance needs of professional scenarios.

The invention discloses a rapid magnetic resonance imaging reconstruction and segmentation method and system, a medium and a product, and relates to the technical field of image processing. The method comprises the following steps: decomposing original three-dimensional magnetic resonance data into a plurality of independent two-dimensional magnetic resonance data slices along a slice sequence; image reconstruction is carried out on the two-dimensional magnetic resonance data slices through a pre-trained forward generator in the frequency domain Schrodinger bridge diffusion model so as to generate a two-dimensional magnetic resonance image, and the forward generator integrates a Fourier convolution module and is used for carrying out frequency domain transformation and feature enhancement processing on feature mapping in the image reconstruction process; inputting each two-dimensional magnetic resonance image into a pre-trained segmentation model in sequence, performing segmentation of a target region and a preset dangerous organ, and generating a corresponding two-dimensional segmentation mask; all the two-dimensional segmentation masks are rearranged and stacked according to the slicing sequence, and a three-dimensional segmentation result is generated through three-dimensional fusion operation. By implementing the technical scheme, magnetic resonance imaging reconstruction and segmentation can be quickly and accurately carried out.

The present invention belongs to the field of medical image processing, and provides a method, system and medium for processing medical endoscopic images based on GPU. The present invention utilizes the powerful parallel processing capability of GPU to significantly improve the speed and accuracy of endoscopic image acquisition, preprocessing, feature point detection, image correction and pathological feature recognition. The image quality is enhanced by executing GPU-accelerated filtering algorithms and histogram equalization, while the GPU-optimized SIFT algorithm effectively improves the accuracy of feature point matching. The estimation of the affine transformation model and the transformation correction of the image further correct the distortion and ensure the accuracy of the image data. Finally, the pre-trained deep learning model is used to implement fast convolutional neural network forward propagation on the GPU, identify pathological features in real time, and assist clinical diagnosis. The efficiency and accuracy of clinical diagnosis are greatly improved, providing doctors with instant diagnostic assistance, thereby improving the quality of medical services.

The application discloses a kind of thermosensitive microcapsule dispersions and its preparation method and application, it is related to microcapsule technical field.The application provides a kind of thermosensitive microcapsule dispersion, the thermosensitive microcapsule dispersion D90≤0.75 μm, thermosensitive microcapsule dispersion D100≤1.35 μm;The thermosensitive microcapsule dispersion includes thermosensitive microcapsule, the thermosensitive microcapsule includes capsule wall and capsule core, the weight percentage of the capsule wall and capsule core is (45-66) :(34-55);The capsule wall is polyurethane-polyurea compound, and the capsule core is chromogenic dye precursor and solvent.The application innovatively generates polyurethane-polyurea compound capsule wall by twice polymerization reaction, by capsule wall material polyisocyanate and polyether polyhydric alcohol primary polymerization reaction, polyisocyanate and polyamine secondary polymerization reaction, by the effective regulation of product species and generation amount, effectively control the temperature sensitivity of thermosensitive microcapsule, color range.

The invention relates to the technical field of scanning devices, in particular to a quick response X-ray scanning device based on a micro-electro-mechanical chip, which comprises a detection table, a photoelectric sensor is arranged in the detection table, a plurality of positioning blocks are arranged on the detection table, and a table top of the detection table is used for bearing an object to be imaged; the X-ray source is arranged above the detection table and can emit X-rays to the direction of the detection table, and the X-ray source is connected with a movable support capable of driving the X-ray source to move; the detector is connected with the detection table and can receive the X-rays penetrating through the object to be imaged and convert the X-rays into digital signals; the detection table fixes the position of an object to be imaged through the positioning block, the image acquisition module acquires an image of the detection table, and the control module adjusts the position of the X-ray source according to the position of the object to be imaged on the image so as to completely scan the object to be imaged. By accurately positioning the position of the object to be imaged and standardizing the image of the object to be imaged, the accuracy and reliability of the whole scanning process are improved, and the scanning efficiency and the imaging quality are improved.

The invention relates to the technical field of electronic component authenticity verification. The invention relates to an electronic component authentication method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining a real-time electronic component image, carrying out the reconstruction of the real-time electronic component image through a trained ESPCN model, obtaining a processed electronic component image, carrying out the feature extraction of the processed electronic component image through a trained CNN model, and obtaining a feature extraction result. And generating a depth feature vector of the to-be-authenticated electronic component, comparing the depth feature vector of the to-be-authenticated electronic component with a standard feature vector in the standard feature database, calculating the similarity to obtain an electronic component similarity value, and judging the authenticity of the electronic component according to the electronic component similarity value to obtain an electronic component authentication result. The method and the device have the effect of quickly and accurately judging the authenticity of the electronic component.

The invention belongs to the field of space target imaging, and discloses a space target three-dimensional reconstruction method for inhibiting dark color interference through combination of brightness and transparency, which is used for solving the problems of poor imaging quality and inaccurate pose estimation of a space target. According to the method, multiple requirements of improving the quality of an input image, adjusting a pose and training a three-dimensional model are jointly completed, and low-quality imaging of an incomplete imaging system is preprocessed based on lucky imaging; and then, dense feature points are extracted by using a pre-training network based on no detector, estimation of a three-dimensional initial point cloud and an initial pose of a camera is carried out, and pose joint adjustment is carried out by combining RANSAC and Bundle AdJustlement. During training, an MLP-based optimizer is used for calculating the deviation of pose adjustment, meanwhile, training of parameters of three-dimensional Gaussian primitives is carried out, and after various physical constraints are added, a one-stop assembly line can be implemented. According to the method, the good basic shape and the sharp edge of the model are kept, the good anti-noise capability is achieved, and meanwhile the real-time performance and the robustness are achieved.

The utility model relates to the technical field of transformer substations, and discloses a transformer substation inspection device which comprises a support, land walking assemblies are arranged on the outer walls of the two sides of the support through chain wheels, an inspection body is fixedly assembled on the top of the support, and one end of a machine arm is fixedly assembled on the outer wall of the inspection body. And an upper propeller is fixedly mounted at the other end of the vehicle arm. A clamping groove is connected with a driving wheel in a clamped mode, so that a clamping block can make contact with the ground, common obstacles can be easily handled, the device can be suitable for various terrains, a damping spring and a damping rod are arranged, and the damping performance of the device can be high by connecting a mounting clamping block with a driven wheel; when an obstacle difficult to surmount is encountered, the upper propeller and the lower propeller can be connected through the mounting piece and then combined to generate lift force to drive the device to lift off, so that the device can achieve the ground and air dual-purpose effect, and the practicability is higher.

The application discloses a ceramic tile cloth powder control method and system, and relates to the technical field of ceramic tile production. The method comprises the following steps: acquiring ceramic tile pattern data required for current production; converting the ceramic tile pattern data into bitmap data, and performing pixel optimization on the bitmap data according to a preset pixel optimization rule to obtain bitmap data of a target resolution; performing partition processing on pixel points in the bitmap data to obtain pixel region data after partition; pairing the pixel region data with a preset cloth powder control database to obtain cloth powder control data of a discharging mechanism; and controlling the discharging mechanism to perform automatic discharging work according to the cloth powder control data, so that powder fills corresponding cloth regions, thereby forming a ceramic tile powder layer with a required pattern. The application can adapt to the production requirement of rapid switching of ceramic tile patterns, has high production efficiency, and the texture and color effect of the produced ceramic tiles are good.

According to the multi-input hierarchical infrared image super-resolution reconstruction method based on the collaborative CNN and Transform, through ingenious combination of the advantages of the CNN and the Transform, clearer detail information and edge structures can be reconstructed in a reconstruction task of an infrared image super-resolution image, the contrast ratio and definition are improved to a certain degree, and the reconstruction efficiency of the infrared image super-resolution image is improved. Unnecessary artifacts and noise are reduced, a clearer appearance is kept while high-precision textures and structures are recovered, and a good visual effect is achieved.

The invention belongs to the technical field of image processing, and particularly discloses an image processing method and system based on histogram matching. Comprising the following steps: separating an original image into RGB channels, and respectively calculating histograms of the channels; calculating the cumulative distribution probability density of each channel according to the histogram of each channel; selecting the channel with the maximum energy as a standard channel, matching histograms of other channels to a standard histogram, obtaining a mapping curve of each channel, and obtaining a gain curve of each channel according to the mapping curve of each channel; calculating the gain of each channel according to the sigma principle and the gain curve of each channel; and respectively adjusting the RGB channels by using the calculated gains to obtain an image after white balance processing. According to the method, the linearity of the image is kept while histogram matching is carried out, so that effective white balance adjustment of the image is realized, and excessive change of source image information is avoided.

The application discloses a kind of based on multi-level supervision attention mechanism super network and random erasing data enhancement's occluded face image super resolution method, comprising: face region cutting, random erasing face content and size adjustment are carried out to public face dataset, construct low-resolution occluded face / high-resolution unoccluded face image pair dataset, and multiple data enhancements are carried out to training set;Multi-level supervision attention mechanism face image super resolution network based on face structure priori guide is constructed;Multi-level supervision attention mechanism face image super resolution network based on face structure priori guide is trained on training set;Low-resolution occluded face image in test set is carried out super resolution.This application overcomes the existing face super resolution method in processing accompanying occlusion input low-resolution face image when result image structure distortion, the problem of detail accompanying artificial artifact, can reconstruct structure complete, accurate, high-resolution face image with high fidelity.

The present application belongs to the field of scene reconstruction, and particularly relates to a 3DGS rendering method and system for HDR large scenes, comprising: acquiring a multi-exposure image sequence and camera pose parameters of a target scene; reconstructing a high dynamic range light field to obtain light field configuration data comprising a dynamic range compression curve, indoor and outdoor area segmentation masks, and a material reflectivity model; iteratively optimizing spherical harmonic coefficients of a Gaussian sphere in a three-dimensional Gaussian splatting model according to the light field configuration data until the area proportion difference between overexposed and underexposed regions is less than a first threshold value; real-time rendering and collecting pixel-level brightness distribution, calculating the average brightness ratio of overexposed and underexposed regions, and if the ratio is less than a second threshold value, directly outputting, otherwise adjusting the spherical harmonic coefficients and tone mapping operators and re-rendering until the requirements are met. Through the light field guided spherical harmonic coefficient optimization and real-time dynamic adjustment, the present application effectively solves the overexposure, underexposure and light and shadow abrupt change problems in HDR scenes, and significantly improves the visual realism and consistency of large scene virtual roaming.

This invention discloses an underwater image enhancement method based on cascaded correction and multi-scale fusion, mainly including the following steps: (1) establishing an underwater image dataset to form a first dataset; (2) constructing an underwater image enhancement model based on cascaded correction and multi-scale fusion; (3) inputting the first dataset into the model for image enhancement; (4) evaluating the enhanced underwater image to meet the index requirements, thus obtaining the final underwater image enhancement model based on cascaded correction and multi-scale fusion. Compared with the prior art, the underwater image enhancement method disclosed in this invention significantly enhances the clarity and color fidelity of underwater images, effectively improving the visual quality of underwater images.

The invention provides a magnetic resonance image super-resolution reconstruction method and device and a terminal, and the method comprises the steps: inputting an obtained to-be-reconstructed low-resolution magnetic resonance image into a trained magnetic resonance image super-resolution reconstruction model, so as to reconstruct a corresponding high-resolution magnetic resonance image; the magnetic resonance image super-resolution reconstruction model comprises a shallow feature extraction module, a deep feature extraction module, a residual error and feature fusion module and a reconstruction module, wherein a high-low frequency feature fusion unit and a high-frequency feature guide unit are introduced into the deep feature extraction module. According to the method, the corresponding high-resolution magnetic resonance image can be obtained only by scanning the low-resolution magnetic resonance image, so that the scanning time is shortened, and the scanning efficiency is improved; the parameter quantity is effectively reduced, so that the network is lighter, and equipment with limited hardware resources is more friendly; the reconstruction model can better utilize high and low frequency features, thereby obtaining a high-resolution image with clear details and real organization structure features.

The application discloses a mahjong machine with a control lighting lamp, and belongs to the technical field of mahjong machines, and has the technical scheme as follows: the mahjong machine comprises a mahjong machine main body, irradiation lamp strips are rotationally arranged on four sides of the mahjong machine main body, placing areas for placing mahjong hands are arranged on the four sides of the mahjong machine main body, the light beams of the irradiation lamp strips are obliquely shot from bottom to top to the mahjong hands in the corresponding placing areas, a controller is arranged on the mahjong machine main body, human body sensing modules are arranged on the four sides of the mahjong machine main body, the human body sensing modules are electrically connected with the controller, the controller is electrically connected with the irradiation lamp strips, when the human body sensing modules sense a human body, the controller controls the corresponding irradiation lamp strip to be turned on, and the four sides of the mahjong machine main body are provided with adjusting knobs for adjusting the brightness of the corresponding irradiation lamp strips, the mahjong machine forms effective light zones on the mahjong hands through the irradiation lamp strips, the recognition of the mahjong hands by users is enhanced, and the use experience is improved.

The present invention discloses an infrared and visible light image fusion system and method, wherein the image fusion system comprises a multi-scale feature extraction unit for respectively extracting features of infrared images and visible light images, a feature screening unit and an image reconstruction unit located after the multi-scale feature extraction unit. Firstly, the multi-scale features of the infrared image and the visible light image are respectively extracted by the multi-scale feature extraction unit, and then the multi-scale features are feature screened by a dual attention mechanism, and then the image reconstruction unit completes the image fusion, thereby obtaining an infrared and visible light fusion image with clear details.

The invention discloses a user authentication method and system for an online education platform, and solves the problem that the existing method adopts frame-by-frame analysis of a face image, can only simply perform independent processing on each frame, and is sensitive to interference information, and the method comprises the following steps: performing normalization processing on target image information to obtain normalized target image information; a multi-target recognition model is constructed in combination with a multi-layer space displacement sensing mechanism and a cascade attitude regression model, the multi-target recognition model carries out noise reduction processing on target image information and then segments and extracts feature points, and the confidence degree of the target image information and the face standard image is calculated; according to the method, the attention of a background information dispersion model can be overcome through normalization processing of the target image information, background interference factors can be rapidly removed, the multi-target recognition model approximates a real face shape and a feature point position through a clustering analysis mode, correction, noise reduction and optimization are carried out on a result of a previous level, and the accuracy of face recognition is improved. Therefore, the positioning precision of the feature points is improved.

The invention discloses a large-aperture large-depth-of-field short-wave infrared vehicle-mounted lens which is applied to a short-wave infrared spectrum band. Comprising a lens L1 with negative focal power, a lens L2 with negative focal power, a lens L3 with positive focal power, a diaphragm STOP, a lens L4 with negative focal power, a lens L5 with positive focal power, a lens L6 with positive focal power and a lens L7 with positive focal power which are sequentially distributed from an object plane to an image plane, and the total optical length TTL, the effective aperture D and the total focal length f of the vehicle-mounted lens meet the conditions that f / D is larger than or equal to 1.4 and smaller than or equal to 1.8, and f / TTL is larger than or equal to 0.1 and smaller than or equal to 0.2. According to the vehicle-mounted lens, the design of large aperture and large depth of field is adopted, the vehicle-mounted lens is more suitable for a long-distance, large-range and low-illumination environment, and clear imaging can be achieved within the object distance range from 0.75 m to infinity without refocusing.

The invention relates to the technical field of biological medicine, and discloses a multi-immunohistochemical staining and field E staining combined comprehensive identification method, which comprises an image data acquisition module, a data analysis module, a data identification module and a data management module, the data analysis module calculates a data speed increase index Siy, a multi-immunohistochemical staining combined field E staining recognition accuracy index Ziy and a comprehensive efficiency increase index Wiy, the data recognition module judges the data transmission speed of the system according to the speed increase index Siy, and the data transmission speed of the system is judged according to the multi-immunohistochemical staining combined field E staining recognition accuracy index Ziy. The data accuracy after the multi-immunohistochemical staining unit and the field E staining unit are combined to work is judged, the comprehensive efficiency of the system is evaluated according to a comprehensive efficiency improvement index Wiy, and the data management module automatically issues a repair instruction to a unit area needing to be repaired according to the judgment data of the data identification module.

The visual enhancement method of a real scene that simultaneously removes haze and improves resolution described in the present invention first uses a rank-one prior to obtain an initial defogging picture and a scattered light map, and then combines the rank-one prior defogging and a super-resolution deep neural network prior for processing various image degradation problems under the framework of a variational model, and uses a semi-quadratic splitting (HQS) optimization algorithm to alternately iteratively estimate the scattered light map for removing haze and seek a high-quality visual enhancement image through a deep super-resolution network. The method described in the present invention can also handle other complex scenes and improve the clarity and recognizability of the acquired image.