17results about How to "Reduce image noise" patented technology

The invention relates to the technical field of laser welding, in particular to a laser welding system control method for metal accessories. The method comprises the following steps that automobile industry metal fitting data are obtained, welding demand analysis is conducted according to the automobile industry metal fitting data, and therefore welding demand data are obtained; laser welding feature extraction and resistance spot welding feature extraction are carried out according to the welding demand data, so that laser welding data and resistance spot welding data are obtained; carrying out welding simulation according to the laser welding data and the resistance spot welding data so as to obtain welding simulation data; welding form feature extraction and welding strength feature extraction are carried out according to the welding simulation data, so that welding form data and welding strength data are obtained; and carrying out welding defect detection according to the welding form data and the welding strength data so as to obtain welding defect data. Automatic adjustment and accurate control of the laser welding process are achieved based on the laser welding technology.

The invention discloses a glaucoma distinguishing detection method and system based on multi-modal fusion. The method relates to the technical field of glaucoma distinguishing detection, and comprises the following steps: collecting glaucoma distinguishing detection data; analyzing glaucoma distinguishing detection data; and comprehensively analyzing, optimizing and adjusting the glaucoma distinguishing detection data quality accuracy. The glaucoma distinguishing detection data is collected and processed, the glaucoma distinguishing detection data is analyzed, the glaucoma distinguishing detection data integrity evaluation index and the glaucoma distinguishing detection data image quality evaluation index are obtained, and the glaucoma distinguishing detection data quality accuracy method is comprehensively analyzed, optimized and adjusted. The accuracy of the glaucoma distinguishing and detecting method and system based on multi-modal fusion is improved, and the problem that the accuracy of the glaucoma distinguishing and detecting method and system based on multi-modal fusion is insufficient in the prior art is solved.

The invention provides a high-signal-to-noise-ratio long-wave infrared multispectral imaging system and an imaging method thereof, which are used for detecting and identifying infrared weak and small targets under a dense fog condition. A dark channel prior method is adopted to carry out defogging processing on each acquired spectrum image so as to eliminate imaging quality degradation caused by atmospheric scattering and absorption; a block matching technology is used for carrying out block matching on a defogged image, similar blocks in a multispectral image are extracted, a collaborative filtering technology is combined for processing the similar blocks, noise is removed, the contrast ratio of the image is enhanced, and the signal-to-noise ratio is doubled. According to the multispectral imaging system, the imaging quality can be effectively improved by utilizing spectral feature differences of different objects and combining an image processing technology, and the multispectral imaging system has high anti-interference performance, is beneficial to foggy day target detection and recognition and has wide application prospects.

The present invention discloses a glaucoma differentiation detection method and system based on multimodal fusion. The method relates to the technical field of glaucoma differentiation detection, and includes the following steps: collecting glaucoma differentiation detection data; analyzing glaucoma differentiation detection data; and comprehensively analyzing and optimizing the method for adjusting the quality accuracy of glaucoma differentiation detection data. The present invention collects and processes glaucoma differentiation detection data, analyzes the glaucoma differentiation detection data, obtains a glaucoma differentiation detection data integrity assessment index and a glaucoma differentiation detection data image quality assessment index, comprehensively analyzes and optimizes the method for adjusting the quality accuracy of glaucoma differentiation detection data, thereby improving the accuracy of the glaucoma differentiation detection method and system based on multimodal fusion, and solving the problem of insufficient accuracy of the glaucoma differentiation detection method and system based on multimodal fusion in the prior art.

The utility model relates to the technical field of light guide illumination equipment, aims to solve the problems that an existing shadowless light illumination system is poor in anti-pollution effect, and illumination images of an acquisition system are prone to interference after the front surface and the rear surface of protective glass have defects or are polluted, and provides an anti-pollution plane shadowless light illumination system. Comprising a light guide panel and protective glass, the protective glass is arranged on the upper side and / or the lower side of the light guide panel and used for protecting the light guide panel, and a lighting source is arranged on the side face of the light guide panel and used for generating light and coupling the light into the light guide panel. The light guide panel converts light transmitted in the light guide panel in a total reflection mode into light output downwards so as to illuminate an object. A light source blocking layer is arranged on the protective glass and is used for preventing light from entering the protective glass; according to the utility model, the identification and detection of defects on the surface of an object caused by defects or dirt interference on the surface of the protective glass are avoided, and the image interference of pollutants on an acquisition system is reduced.

The invention relates to the technical field of underwater exploration, in particular to an underwater portable imager which comprises an imager body, a display screen, a disc, a holding rod, a connecting rod, a fixing ring and the like. A detection head is arranged on the lower side of the imager; a display screen is mounted on the front side of the imager; a plurality of discs are fixedly connected to the imager; a holding rod is mounted on each disc; the lower side of each holding rod is connected with a connecting rod; a locking device is connected between each connecting rod and the adjacent holding rod; a protruding rod is arranged on each connecting rod; a plurality of fixing rings are fixedly connected to the lower side of the imager; each protruding rod is connected with the adjacent fixing ring in a clamped mode. The aquatic plants on the front side of the imager are pushed aside to the left side and the right side through the two holding rods respectively, so that soil in an area with the aquatic plants is exposed below a detection head, imaging interference of floating of the aquatic plants on the imager is reduced, and the imaging quality of the imager during underwater movement detection is improved.

The invention provides a novel fixing device for mouse brain imaging. The novel fixing device comprises a first fixing assembly, the bottom of the first fixing assembly is connected with an adjusting platform, the bottom of the adjusting platform is connected with a mounting bottom plate, a second fixing assembly is arranged on the mounting bottom plate, and one end of the second fixing assembly is close to the first fixing assembly; the first fixing assembly comprises an inverted-T-shaped plate, the inverted-T-shaped plate is installed at the top of the adjusting platform, two supporting cylinders are symmetrically arranged at the positions, close to the second fixing assembly, of the inverted-T-shaped plate, the top of each supporting cylinder is movably connected with a first connecting plate, a brain fixing piece is connected between the two first connecting plates, and the brain fixing piece is fixed to the head of a mouse. A positioning hole is formed in the brain fixing piece and used for positioning a window area for mouse brain imaging. According to the device, the stress reaction of the mouse in the experiment process is relieved, the reliability and repeatability of the experiment are improved, the absolute stability of the mouse in a waking state is ensured, and the accuracy of experiment data is effectively improved.

The invention discloses a heart interventional operation scene low-light enhancement method and system based on a diffusion model, and aims to solve the problem of unclear operation view in a low-light environment. Multi-angle low-light images are acquired through a micro camera and an external camera system, and enhancement processing is performed by using a diffusion model optimized for a cardiac interventional operation scene. The diffusion model adopts two low-light image sources with different scales and angles as a training data set so as to capture image details of different levels from microcosmic to macrocosmic. By performing the diffusion process under different resolutions, the micro structure and the overall tissue layout in the surgical field of view can be more accurately reconstructed. A noise scheduling value is dynamically adjusted by introducing prior knowledge related to a cardiac interventional operation, and illumination parameter prediction is performed to guide optimization of diffusion model parameters, so that the diffusion model can more accurately improve the image quality of an operation area in real time.

The present application provides a banknote anomaly detection method and system based on big data, which relates to the field of intelligent detection. It extracts hue features and content semantic features of optically variable ink areas by applying image processing and analysis algorithms based on artificial intelligence and deep learning technology, so as to depict the hue and content semantic feature information of the optically variable ink area, and detects whether the banknote is an abnormal banknote based on the significant sparse interactive fusion representation between the two hierarchical features of the optically variable ink area. In this way, it is possible to capture multiple features of the banknote more comprehensively, avoid the influence of ambient lighting conditions when performing banknote anomaly detection, reduce the influence of image noise and processing errors, thereby more comprehensively identifying abnormal banknotes and improving the accuracy of detecting whether the banknote to be detected is an abnormal banknote.

The invention relates to an image processing method and device, electronic equipment and a storage medium. The image processing method comprises the steps of obtaining current exposure information in response to an image preview request for a to-be-collected object in a high-dynamic photographing mode; under the condition that the to-be-collected object is in a target motion state, adjusting the current exposure information to obtain target exposure information; and performing exposure processing based on the target exposure information to obtain a preview image for the to-be-collected object. According to the image processing method provided by the embodiment of the invention, under the condition that the to-be-collected object is determined to be in the target motion state, the image exposure processing is performed through the target exposure information, so that imaging noise introduced by motion of the to-be-collected object can be reduced, and the imaging effect of the moving object with a dynamic range is improved.

The present invention provides a high-precision multi-view image rendering method for a light field camera, which ensures the efficiency and accuracy of multi-view image rendering through the following processing steps. First, in step S1, the center of each microlens image MI is accurately located. Then, in step S2, based on the center positioning result, the MI edge brightness attenuation is compensated to improve the spatial resolution. Step S3 dynamically estimates and adaptively adjusts the image block patch size to ensure continuity and consistency during stitching. Finally, step S4 extracts and accurately stitches the image blocks according to the estimated size to generate a multi-view image with rich details and no visual artifacts. The whole process optimizes brightness uniformity, size adaptability and stitching accuracy, providing an innovative solution for multi-view image rendering.

An embodiment of the present invention provides a method, storage medium and electronic device for adjusting image noise, comprising: obtaining target brightness values ​​of various regions of a target image, wherein the target image is divided into multiple regions, each region includes at least one pixel, and the target image is an image obtained by adjusting the brightness of an original image; obtaining noise magnitudes of various regions obtained by performing an i-th noise adjustment on the target image, wherein i is an integer greater than or equal to 0; determining adjustment state parameters of various regions according to the target brightness value and the noise magnitude, wherein the adjustment state parameters are used to indicate whether various regions require an i+1th noise adjustment; and when the adjustment state parameters of the target region indicate that the target region requires an i+1th noise adjustment, adjusting the noise magnitude of the target region according to the adjustment state parameters and the target brightness value of the target region, wherein the multiple regions include the target region.

The present invention relates to the field of visual inspection technology, and discloses a processing method for industrial camera acquisition, comprising the following steps: Step 1, start the industrial camera, initialize basic parameters, enable the intelligent automatic exposure control system, and preliminarily set the exposure time and gain parameters; Step 2, use the developed exposure control algorithm based on image analysis to analyze the initial image data in a low-light environment in real time, and dynamically adjust the exposure parameters of the camera according to the image brightness and details; Step 3, continuously acquire multiple frames of low-light images in a short time. By developing a deep neural network model specifically for low-light environments, it can automatically learn and optimize the features of low-light image processing, effectively improve the clarity and detail performance of the image, and adopt multi-frame information fusion technology to combine multiple frames of low-light image data for image reconstruction and enhancement, which can significantly reduce image noise, enhance image details, and generate clearer and higher-quality image output.

The present application belongs to the field of multi-modal named entity recognition, and particularly relates to a power equipment multi-modal named entity recognition method, system, device and medium. The present application adopts a co-occurrence entity method to obtain entities appearing in both text and images, which can ensure text and image matching and reduce image noise. By extracting entity triples and then adopting an entity auxiliary method, semantic information can be supplemented and semantic disambiguation can be reduced. The present application adopts the co-occurrence entity and entity auxiliary method of extracting triples, which helps to improve the multi-modal named entity recognition accuracy, accurately recognize the entities existing in the image or text, and especially performs better in data with higher image-text correlation. Meanwhile, the present application is not limited to the field of power equipment, and can be constructed into a knowledge base of other fields to expand to other fields for multi-modal named entity recognition.

The invention relates to the technical field of radars, and provides a laser radar and automatic driving equipment. The laser radar comprises a first transmit-receive module, a second transmit-receive module and a galvanometer. The first transceiver module and the second transceiver module are both used for emitting emergent laser and receiving echo laser, the echo laser is laser returned after the emergent laser is reflected by an object in a detection area, and the galvanometer is used for reflecting the emergent laser emitted by the first transceiver module and the second transceiver module and then emitting the emergent laser to the detection area. Meanwhile, the first receiving and transmitting module and the second receiving and transmitting module are used for reflecting the echo laser and transmitting the reflected echo laser to the corresponding first receiving and transmitting module; the detection areas corresponding to the more than two first transceiver modules are spliced into a scanning area, and the detection area corresponding to the second transceiver module is at least partially overlapped with the scanning area. The detection area corresponding to the second transceiver module is specially used for overlapping with the scanning area, a large-area ROI area can be realized, and the ROI area is formed by adopting a physical overlapping mode, so that network broadband occupation and computing resources are saved.

The application discloses a soldering contour extraction method, device, equipment and storage medium. The method first acquires a two-dimensional image and a three-dimensional height map of a target detection object; performs image segmentation on the two-dimensional image to obtain an initial mask; modifies the initial mask based on height information in the three-dimensional height map to obtain a target mask; extracts an edge of the target mask to obtain a closed contour point sequence; performs geometric fitting on the closed contour point sequence to convert the closed contour point sequence into an initial geometric primitive sequence containing line segments and arc line segments; performs primitive position alignment and intersection reconstruction on the initial geometric primitive sequence based on a preset geometric rule to obtain a target geometric primitive sequence; and generates soldering contour data of the target detection object based on the target geometric primitive sequence. The application can improve the precision of the extracted contour data and thus improve the accuracy of SPI detection.

The invention discloses a training method and device of a vein recognition model, and relates to the technical field of vein recognition, an acquired preset angle range is accurately set to be 0-90 degrees, and image resolution and illumination conditions at different angles are ensured to be consistent through a quasi vein recognition device. The vein images collected at each angle are ensured to have consistent quality, the problems of image noise and feature loss caused by illumination variation or inconsistent equipment resolution are reduced, the definition and stability of the images are improved, the collected vein images are processed by using a Gaussian filtering denoising algorithm, and the image quality is improved. And noise introduced by equipment or an external environment is removed. According to the method, the image can be smoothed through Gaussian filtering, the image noise is effectively reduced, the image quality is improved, the instability in the image collection process is reduced through multi-angle collection and consistent illumination conditions, and the collected images keep high consistency at different angles.