249 results about "Color processing" patented technology

An infrared image processing method, apparatus and device, and a storage medium are provided. The infrared image processing method includes: acquiring an infrared image; performing target detection on the infrared image to determine target objects within the infrared image and obtaining a target detection result that include a category of each of the target objects; determining a target object of interest from the target objects; determining a contour area of the target object of interest; performing true-color processing on the contour area to highlight the target object of interest. By highlighting the target object of interest in the infrared image through true-color processing, the target object of interest can be displayed more prominently with different colors and textures according to its category, so that the target object of interest can be presented more clearly in the infrared image clearer and easier for the human eye to observe and recognize.

The invention discloses a vision and line structured light fused underwater three-dimensional measurement method. The method comprises the following steps: step 1, preprocessing an acquired image; 2, system parameter calibration is carried out on the preprocessed in-air color calibration image and the preprocessed in-air center line structure light calibration image, and internal and external parameters of a camera and a line structure light plane equation are obtained; 3, establishing a three-dimensional refraction model for the underwater color three-dimensional measurement object image and the underwater line structure light measurement object image, and performing affine transformation of the three-dimensional refraction model; 4, performing laser line center extraction on the transformed underwater line structured light measurement object image, and substituting the laser line center into the calibrated line structured light plane equation to perform point cloud reconstruction; and step 5, performing color processing on the underwater color three-dimensional measurement object image, and mapping the image to three-dimensional point cloud data. According to the invention, through affine transformation of the multi-medium refraction image and point cloud mapping of color multi-channel equalization, the precision and visual effect of underwater three-dimensional measurement are significantly improved.

The invention provides a mobile phone screen color gamut control method and system, and the method comprises the steps: collecting the spectral characteristics of ambient light, and constructing a spectrum matrix; constructing a dynamic reference color model based on the spectrum matrix to generate a global color gamut adjustment matrix, and dynamically adjusting the screen color gamut according to the global color gamut adjustment matrix; collecting eye movement data of a user in real time, constructing a fixation area, and performing area color gamut optimization analysis on the fixation area in combination with the dynamic reference color model; according to an optimization analysis result, local compensation is carried out in combination with the global color gamut, and a final local color gamut matrix is generated; the energy consumption of the non-gazing area is reduced, and unnecessary color processing is reduced. The invention provides an intelligent and dynamic color gamut self-adaptive adjusting system by combining environment spectrum detection and eye movement tracking technologies, overcomes the defects of the prior art in the aspects of environment light adaptability, color accuracy and energy efficiency, and has remarkable innovativeness and practical value.

The invention belongs to the technical field of image processing, and discloses an improved DCGAN-based pipeline magnetic flux leakage defect image generation model, which comprises the following steps: S1, acquiring a magnetic flux leakage signal in a pipeline through a magnetic flux leakage detector; s2, carrying out image enhancement by adopting a pseudo-color processing technology, and carrying out pseudo-color enhancement by adopting density segmentation; s3, a residual network and an attention mechanism are embedded into the DCGAN model, and the extraction capability of model features is improved; and S4, generating a pipeline magnetic flux leakage defect image through the improved model. The algorithm proposed by the pipeline magnetic flux leakage defect image generation model based on the improved DCGAN can stably generate a pipeline magnetic flux leakage defect image with better quality, an effective way is provided for expansion of a pipeline magnetic flux leakage defect sample data set, and the problem of small samples faced by development of deep learning in the field of defect detection can be effectively solved.

This invention provides an image processor, a processing method, a storage medium, and a mixed reality display system. The image processor includes: a first color management module, whose input is connected to a rendering module, for acquiring virtual layer data from the rendering module and performing first color processing on it; a second color management module, whose input is connected to a camera module, for acquiring real-world layer data from the camera module and performing second color processing on it; a layer blending module, whose inputs are respectively connected to the first and second color management modules, for performing layer blending processing on the color-processed virtual layer data and real-world layer data to determine mixed image data; and a third color management module, whose input is connected to the layer blending module, for acquiring mixed image data from the layer blending module, performing third color processing on it, and outputting the third-color-processed mixed image data to a mixed reality display.

The invention discloses a multi-scene SAR image uniform color processing method and device considering terrain radiation, and belongs to the technical field of remote sensing image processing, and the method comprises the steps: obtaining an SAR image of a to-be-detected region, carrying out the preprocessing of the obtained SAR image, and extracting a sampling point; the sampling points are substituted into a sinc function model, global optimization is carried out by fitting the overall SAR image of the to-be-detected area, and a global sinc function compensation coefficient is obtained; constructing polynomial fitting for each original SAR image in the to-be-measured region by using the idea of block adjustment, and integrally calculating polynomial model correction parameters of all SAR images; and performing uniform color correction on the original SAR image in combination with the global sinc function compensation coefficient and the polynomial correction coefficient. According to the method, the problems of path error propagation and accumulation, color difference residue in an overlapping region and the like generally existing in an existing color equalization processing method are effectively avoided, and an effective way is provided for uniform color processing of the SAR image.

The invention relates to the technical field of intelligent inspection, in particular to a transformer substation unmanned aerial vehicle local area network automatic inspection method and system based on laser point cloud. The method comprises the following steps: firstly, obtaining three-dimensional point cloud data of a transformer substation through an unmanned aerial vehicle carrying a laser radar, and constructing an accurate spatial information model through calculation and color assignment processing; automatically identifying the equipment type based on the model, and generating an initial route according to a power grid inspection procedure; setting inspection parameters including flight height, speed, angle and the like, and optimizing an inspection route; then test flight verification is carried out, and the inspection result is evaluated by comparing a photographing result with a preset standard; when a problem is found, the system automatically triggers an adjustment instruction, obtains a correction parameter and determines a final inspection route; through three-dimensional space perception, intelligent planning and dynamic optimization, the accuracy and reliability of substation unmanned aerial vehicle inspection are effectively improved, and meanwhile, a complete quality guarantee mechanism is established.

The invention discloses an explosion-proof full-color low-light night vision camera for mines, which comprises an explosion-proof shell, an explosion-proof lens, an image sensor, an image processing module and an image transmission module, and is characterized in that the image processing module comprises an image acquisition module used for acquiring multiple frames of original low-light images in a low-illumination environment based on an enhanced image sensor; the image noise processing module is used for processing the multiple frames of original low-light images through a noise suppression algorithm so as to remove noisy points in the images; the image color processing module is used for generating a full-color night vision image which is accurate in color and rich in details based on an image fusion and color compensation technology; and the image optimization module is used for performing real-time optimization processing on the full-color night vision image to improve the frame rate and the recognition effect of the target in the low-contrast environment. The camera can solve the problem that a high-definition full-color picture cannot be displayed even if light supplement is adopted in a night vision environment.

The invention relates to the technical field of semiconductor manufacturing, and discloses a component offset detection method and device and electronic equipment. The method comprises the steps of obtaining a target image of a to-be-detected component, and performing positioning detection according to the target image and a template image to obtain a reference point image and a pin image on the target image; according to the reference point image and the pin image, detecting whether the position offset of the reference point and the pin is within a preset range; and if the position offset is within the preset range, carrying out image line segment detection on the pin image to obtain an angle of a pin in the to-be-detected component, and determining whether the to-be-detected component deviates or not based on the angle of the pin. The method does not depend on a color extraction algorithm, errors caused by difficult color processing are reduced, and the accuracy and stability of offset detection are improved; the method is suitable for various types of components, more direct and accurate deviation judgment is provided for angle information, and flexibility is achieved so as to adapt to design and manufacturing of different PCB cards.

The invention provides an image processing method, device and equipment based on gas imaging, and is applied to the technical field of image processing. The method comprises the following steps: collecting a gas imaging image and a visible light image for a target scene; for each frame of gas imaging image, detecting a gas mass, a gas position mapping table and a gas confidence coefficient table in the gas imaging image according to a preset gas detection model to obtain a gas detection result; aiming at a gas detection result, acquiring a foreground frame with a gas mass and an initial background frame without the gas mass, and determining a real background frame based on the initial background frame and a corresponding weight coefficient; according to the gas position mapping table, the gas confidence coefficient table and the real background frame in the foreground frame, extracting a gas form concentration graph from the gas imaging image; and performing pseudo-color processing on the gas form concentration graph, and superposing the gas form concentration graph on the visible light image to obtain a gas pseudo-color image. Through the method, the gas extraction precision can be effectively improved, and observation by a user is facilitated.

The invention provides a point cloud coloring processing method and device, equipment and a storage medium, and the method comprises the steps: calculating the timestamp of each pixel line according to the exposure time length and pixel reading time length of a target image under the condition of clock synchronization of a laser radar and a camera, thereby determining the camera pose data of the camera when the camera collects each line of pixels, and carrying out the processing of the point cloud coloring. And further determining the real projection position of each point in the point cloud in the target image, namely, when the projection point under the camera pose data corresponding to a certain pixel row just falls in the pixel row, determining that the projection point at the moment is the target pixel point of the point, and coloring the point cloud by using the target pixel point corresponding to each point. The method can reduce the difference between the point cloud color and the actual color caused by the roller shutter door effect, improves the point cloud coloring accuracy, does not need to use a global shutter camera, and is lower in cost.

The invention discloses a double-stage underwater image enhancement method based on deep learning, which belongs to the technical field of image processing, and comprises the following steps: firstly, acquiring an underwater image data set; and secondly, based on CNN and Transform, constructing a dual-stage mixed underwater image enhancement model, processing an underwater image data set in two stages, and outputting an underwater image enhancement result image. And finally, searching the dual-stage mixed underwater image enhancement model by using the lower image data set, and testing. According to the method, a better clean underwater image can be obtained, detail processing of an object is finer, color processing is appropriate, and a better effect can be generated.

The invention provides an underwater image enhancement method combining multiple color spaces and multiple scales, and belongs to the technical field of image enhancement and deep learning. The method comprises the following steps: processing an underwater image through a color processing channel to obtain color fusion features; processing the underwater image through a scale processing channel to obtain scale fusion features; and fusing the color fusion feature and the scale fusion feature of the underwater image to obtain an enhanced image. According to the method, a multi-color space and multi-scale coordinated double-coding enhancement network is adopted, different color spaces are coded through parallel residual errors in multi-color space coding, and the limitation of a single-color space method on color cast correction, color distortion processing and contrast difference is effectively solved by decoupling color and brightness information. In multi-scale coding, hierarchical feature extraction and cross-scale information complementation are adopted to capture details and texture features of an image on different scales, and blurring and detail loss at different depths can be effectively processed.

This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on a storage medium, for energy-efficient display color processing for static areas on a screen. A processor may obtain a first indication that a first region of a first frame will remain static. The processor may aggregate a second region of each frame in a set of frames following the first frame based on the first indication, where each frame in the set of frames includes the first region to remain static, and where the second region of each frame in the set of frames is different for each frame in the set of frames. The processor may output a second indication of the aggregated second region of each frame in the set of frames.

A fundus color photo image grading method and apparatus, a computer device, and a storage medium are provided. The method comprises: obtaining an original image, enhancing the original image, and obtaining a target image (S100); performing color processing on the original image and the target image, and respectively obtaining a first processed image and a second processed image (S200); using a pre-trained grading model to perform processing on the first processed image and the second processed image, and obtaining a target grading result (S300). Multi-color space first and second processed images act as model inputs, and prediction is performed by means of fused features on a whole image scale to implement the classification and grading of common fundus color photo diseases, so as to automatically screen fundus color photos with pathological changes, achieve a pre-screening effect, and improve operational efficiency.

The invention discloses an infrared image enhancement method and system combining background equalization and detail stretching. The method comprises the steps that an original gray infrared image is decomposed into an image background layer and an image detail layer through an image decomposition method based on a comprehensive average gradient and guided filtering; performing image enhancement processing on the image background layer based on contrast-limited adaptive histogram equalization to obtain an enhanced image background layer; denoising and stretching the detail layer of the image based on adaptive bilateral filtering to obtain a denoised and stretched detail layer; fusing the enhanced image background layer and the denoised and stretched detail layer, and carrying out stretching processing to obtain an enhanced gray infrared image; and performing pseudo-color processing on the enhanced gray infrared image to generate a color infrared image. The method is mainly applied to the technical field of infrared image enhancement, and has wide application prospects in the fields of electrical state monitoring, industrial defect detection and the like. The method has the outstanding advantages of good effect, high practicability, low cost and the like.

The embodiment of the invention provides an industrial camera and an image processing method, and relates to the technical field of machine vision, the industrial camera comprises a spectrum sensor, an image sensor and a processor, when the image sensor collects an original image of a shot object, the spectrum sensor collects spectral information of an ambient light source, and the processor processes the spectral information; and the processor determines a target color correction matrix corresponding to the spectral information in a pre-calibrated color correction matrix database according to the spectral information, and finally performs color processing on the original image based on the target color correction matrix to obtain a target image. By applying the scheme provided by the embodiment of the invention, the industrial camera can automatically acquire the current spectral information of the ambient light source, and perform color processing on the original image based on the color correction matrix corresponding to the spectral information to obtain the target image, so that the adjustment process of the industrial camera is simplified.

The invention relates to a light color control system, a video player, a smart home system and a computer equipment storage medium. The control system comprises an embedded graphic display system which is used for collecting video signals from a video source and obtaining image pictures; the light color processing unit is used for performing color analysis on the image picture to obtain color data; the light address coding unit is used for carrying out address coding on light equipment according to the color data to generate light control parameters, and outputting the light control parameters to a light driver to drive the light equipment to emit light, so that the light color of the light equipment changes along with the image picture output to the display screen by the video player; according to the technical scheme, the equipment cost in light color control is reduced, and the light color control effect is improved.

The present application provides an image processing method, device and electronic device. In the technical solution of the present application, an image to be processed is obtained; the image to be processed is processed by the first branch of a pre-trained neural network model to obtain a first type of parameter, and the first type of parameter is used to perform global color processing on the image; the image to be processed is processed by the second branch of the neural network model to obtain a second type of parameter, and the second type of parameter is used to perform local color processing on the image; the image to be processed is color processed according to the first type of parameter and the second type of parameter to obtain a color-processed image. In the above technical solution, the input of the neural network model is the image to be processed, and different branches output different types of parameters, which can avoid the error accumulation problem in the parameter calculation process and obtain more accurate parameters. Furthermore, the image to be processed is processed according to the obtained parameters, which can improve the image color correction effect.

The embodiment of the application discloses an image processing method and device, relates to the technical field of image processing, and can identify and process white bottom icons, and improves user experience. The specific scheme is as follows: color information of a picture to be rendered is acquired; the color information of the picture to be rendered comprises color categories of the picture to be rendered, color values of four corners of the picture to be rendered, a proportion of non-transparent pixels in the picture to be rendered, and a proportion of white pixels in the picture to be rendered; and based on the color information of the picture to be rendered, if it is determined that the picture to be rendered is a white bottom icon, the picture to be rendered is subjected to inverse color processing.

The invention discloses a geometric processing method and system, a processor, equipment, a medium and a product, and the method comprises the steps: carrying out the first-stage geometric processing of a to-be-processed first vertex, and obtaining a second vertex; performing second-stage geometric processing on the second vertex to obtain data after geometric processing; wherein the geometric processing of the first stage is used for removing the vertexes, which do not need to be subjected to coloring processing, in the first vertexes based on a primitive removal mode, so as to obtain second vertexes; the geometric processing of the second stage is a geometric processing process aiming at the second vertex, and the geometric processing of the first stage lacks the coloring processing compared with the geometric processing of the second stage. Based on the embodiment provided by the invention, the overall performance of geometric processing can be optimized by combining staged vertex elimination and coloring processing.

The invention provides a flora data processing method and device based on a quantitative plate. The flora data on the quantitative plate can be rapidly and accurately obtained. Comprising the following steps: shooting flora images on a quantitative disc through two cameras to obtain color image data; obtaining actual three-dimensional coordinates according to the two-dimensional coordinates of the calibration points in the two pieces of color image data, and obtaining actual three-dimensional coordinates of all the slots according to the actual three-dimensional coordinates; according to the actual three-dimensional coordinates of the hole grooves, cutting and marking the hole groove area where each hole groove is located in the color image data; obtaining the color of each hole slot in the color image data, and carrying out graying processing on the color of each hole slot to obtain a grayed image; performing binarization processing on the grayed image according to a preset threshold value to obtain a binarized image; marking different colors for the corresponding hole slot areas according to the binarized image so as to obtain a color processing picture; and analyzing and identifying the number and positions of blocks of corresponding colors in the color processing picture to obtain flora data.

A camera parameter automatic optimization system for binocular depth estimation, a true value acquisition module acquires a depth true value map in a simulation environment; an Auto-CAM learning module adopts a deep reinforcement learning framework based on an actor-critic, learns in reverse propagation according to a current camera configuration, a state vector generated by left and right view images and a depth error, so as to optimize camera parameters such as focal length, baseline distance and distortion coefficient; a deployment module outputs an optimal camera parameter configuration under a specific scene, a camera calibration module acquires accurate camera parameters through corner scanning, an image acquisition module acquires RGB binocular images, a depth map prediction module outputs a predicted disparity map by using a stereo matching network algorithm and converts the predicted disparity map into a depth map, and finally, a visual rendering module performs filtering and color processing. The application not only improves the accuracy of depth estimation and the adaptability of the system, but also improves the accuracy and efficiency of camera calibration, optimizes the user experience and visual effect.

The invention relates to a color processing method and apparatus, a device, a storage medium and a program product. The method comprises the steps of obtaining a first pixel value of a node in a native color gamut of a display device; performing conversion processing on the first pixel value of the node in the native color gamut based on a conversion function to obtain a second pixel value of the node in the native color gamut; wherein the matching degree between the color composition indicated by the second pixel value and the node is higher than the matching degree between the color composition indicated by the first pixel value and the node; performing conversion processing on the second pixel values of the nodes in the original color gamut based on a preset conversion matrix to obtain coordinate values of the second pixel values of the nodes in the original color gamut in a preset color space; wherein the preset conversion matrix is a conversion matrix for converting the nodes in the original color gamut from the color space where the nodes are located to the preset color space, so that the color distribution condition of the original color gamut of the display equipment is accurately evaluated, and the accuracy of converting the nodes in the original color gamut of the display equipment to the preset color space is improved.

The present application provides a kind of conditional image generation method and related device based on point rasterization, according to the environment image corresponding to target time, target point cloud set is colored processing;The target point cloud set after coloring processing is carried out front and background separation processing, to determine the dynamic foreground region and static background region therein;Combining the historical point cloud set in time window, the incomplete area is completed;Using perspective projection mapping relationship, the target point cloud set after completion is projected to the image coordinate system of vehicle, to obtain first projection image;The raster area in first projection image is rendered, to obtain the conditional image of point rasterization.It is analyzed frame by frame to original laser radar point cloud data and image plane mapping, and combined with point rasterization processing, constructs the geometric conditional image with pixel level precision, provides structure priori support for subsequent new view synthesis and controllable video generation.

The invention relates to the technical field of image processing, in particular to an image processing method, electronic equipment, a readable storage medium and a program product. The method comprises the following steps: detecting a user operation (recorded as a first user operation) for starting quick coloring in an interface of a drawing application running in the electronic equipment, displaying M frames of images recommended to a user, and further determining at least one frame of reference frame image from the M frames of images based on the selection of the user as a coloring reference. The electronic equipment can color the to-be-colored images in the multiple frames of images of the first animation in batches according to at least one frame of reference frame image selected by a user, and colored images corresponding to the multiple frames of images of the first animation are generated. Therefore, when the image sequence containing multiple frames of images (such as animation line manuscripts and the like) is colored, the coloring processing efficiency can be improved.

The application discloses a method for calculating the area of pesticide application. The method comprises the following steps: obtaining the motion trajectory of a pesticide application device, and intercepting a third trajectory located in a first area to be applied with pesticide; obtaining a radiation range according to the third trajectory and the pesticide application range, and performing color processing; calculating the area after color processing to obtain the pesticide application area, and judging the pesticide application condition in combination with a target area. In addition, after the pesticide application is completed, a trajectory point is randomly selected as a detection position, and a corresponding plant image is required to be uploaded for verification. The application solves the area calculation problem of irregular areas and overlapping spraying through a color algorithm, and realizes precise quantitative evaluation and anti-fraud supervision of the pesticide application quality in combination with a random inspection mechanism.

The invention relates to the technical field of photoelectric data processing, provides a light wave chromatography computer coding method, system and architecture based on a toning principle, and aims to break through the performance bottleneck of traditional electronic calculation. According to the method, physical-level color processing is realized through color binary coding and light wave state discrete mapping based on an optical toning principle. The system integrates a digital input interface, a wavelength coding converter, a light wave operation core and a wavelength analysis unit, and supports efficient optical signal direct operation. On the architecture level, an extended von Neumann design is adopted, a three-level Clos-WSS optical interconnection network, a photon ALU and a PCM holographic main memory are included, and femtosecond-level delay, low power consumption and high parallelism are achieved. Advantages include physical level computational accuracy, nearly zero data handling energy consumption, and large scale wavelength level parallel processing. The method is suitable for 8K video real-time color modulation, industrial sorting and other high-requirement scenes, and a subversive solution is provided for the fields of automatic driving, digital twinning and the like.

The present disclosure relates to a character color processing method, device, equipment, and storage medium. The method includes: performing character block detection and character segmentation processing on the title image data of the processing page to obtain the target character block and character segmentation map of the title image data, wherein each character in the target character block corresponds to first binary information, and the character segmentation map contains second binary information of each character; based on the first binary information of each character and the second binary information of each character, determining the target binary information of each character; based on the target binary information of the character, processing the initial color value of each character in the title image data to obtain the target color value of each character in the title image data. In this way, character block detection and character segmentation processing are performed on the title image data at the same time to prevent the problem of missed character detection, and the color of the characters is unified based on the target binary information of each character, so that characters that have not been unified in color will not appear.

The application belongs to the technical field of machining and provides a multi-directional micro-groove structure superposition modulation structural color machining method, which comprises the following steps: determining a first interval between two adjacent first grooves to be machined according to first preset information; machining a plurality of parallel first grooves on the surface of a workpiece according to the first interval; determining a second interval between two adjacent second grooves to be machined according to second preset information; and machining a plurality of parallel second grooves on the surface of the workpiece according to the second interval, wherein the length direction of the first grooves is not parallel to the length direction of the second grooves. The application is conducive to improving the depth of the color presented by the surface of the workpiece and can also present a plurality of different colors, thereby being conducive to realizing more color levels or the display of complex color effects.