167 results about "Pixel color" patented technology

The invention relates to the field of computer vision, and discloses a laser radar and camera joint calibration method, electronic equipment and a storage medium. The method comprises the following steps: acquiring point cloud data of a plurality of laser radars and image data of a camera; performing motion distortion compensation on the point cloud data to generate a global point cloud map; converting the global point cloud map into a plurality of three-dimensional Gaussian voxels with color attributes and covariance attributes; minimizing the first loss function by jointly optimizing the attribute of the three-dimensional Gaussian voxel and the external parameter of the camera so as to complete the calibration of the external parameter of the camera; wherein the first loss function comprises a color consistency constraint term and a rendering error term, and the color consistency constraint term is used for constraining that observed color attributes of a single three-dimensional Gaussian voxel at multiple moments and multiple visual angles are kept consistent; the rendering error term is a pixel color error between a projection image generated by the three-dimensional Gaussian voxel and image data of the camera. Therefore, the precision of external parameter calibration in a dynamic scene is improved.

Embodiments described herein provide a 3D generation system from a single RGB image of an object by inferring the hidden 3D structure of objects based on 2D priors learnt by a generative model. Specifically, the 3D generation system may reconstruct the 3D structure of an object from an input of a single RGB image and optionally an associated depth estimate. For example, a radiance field is formulated to depict the input image in one viewpoint of the target 3D object, based on which other viewpoints of the 3D object can be inferred. Based on the visible surface depicted by the input image, points between the reference camera and the surface are assigned with zero density, and points on the surface are assigned with high density and color equal to the corresponding pixel in the input image.

The invention provides a power equipment three-dimensional modeling and route planning method based on laser point cloud and image fusion. The method comprises the steps that an original point cloud sequence and an original image sequence collected by an unmanned aerial vehicle and pose information of the unmanned aerial vehicle are acquired; preprocessing the original point cloud sequence to generate a clean point cloud sequence; preprocessing the original image sequence to generate an enhanced image sequence; performing rough matching on the clean point cloud sequence according to the pose information to generate a panoramic scene point cloud; projecting points of the panoramic scene point cloud to the enhanced image sequence; mapping the pixel color to the panoramic scene point cloud by applying an L-M algorithm to generate a color point cloud; inputting the enhanced image sequence into a pre-trained SegFormer semantic segmentation model to obtain semantic probability distribution of each image; mapping the color point cloud to a corresponding image according to the semantic probability distribution to generate a semantic point cloud, the semantic point cloud including color information and semantic information; and generating a three-dimensional scene model according to the semantic point cloud to output an inspection route.

The invention relates to the technical field of video compression, in particular to an AI-based video compression platform, which comprises a key target detection module, an image region division module, a coding level setting module, a parameter adjustment and analysis module and a coding result integration module. According to the method, key region extraction is completed by collecting pixel color combination and contour change information in a video frame image, background and non-background region boundaries are delimited, a region attribute labeling result is constructed, a region distribution classification relation mapping coding level is established, and reference frame and prediction interval configuration is extracted. Real-time adjustment of compression levels is realized by performing normalized combination analysis on textures and motion change trends of different regions, and region fragments under different compression levels are recombined and subjected to unified code stream processing, so that coding resources can be dynamically allocated on the basis of accurately identifying contents in a compression process; the problems of inaccurate target positioning, fixed compression configuration, delayed content response and the like in an existing compression system are effectively solved.

The invention provides a printing image processing method, a thermal printing control method and electronic equipment, and the method comprises the steps: extracting the page information of a to-be-printed document, and converting the to-be-printed document into a bitmap according to the page information; obtaining a global threshold value of each pixel point based on the bitmap; sequentially traversing each pixel in the bitmap, for the traversed target pixel, obtaining a region contrast ratio corresponding to the target pixel, and adjusting a global threshold value according to the region contrast ratio to obtain a local threshold value corresponding to the target pixel; and binarizing the corresponding target pixel according to each local threshold to obtain a binarization result. The local threshold is obtained by adjusting the global threshold through the area contrast, the local threshold can better reflect the pixel color close to the target pixel, the problem that the global threshold cannot effectively distinguish the black pixel from the white pixel in the partial area with the low contrast is solved, accurate binarization operation is performed on the target pixel, and the image quality is improved. The contrast between black pixels and white pixels is improved, and the black and white printing effect is improved.

An image highlight removal method and system, a storage medium and a program product relate to the field of general image data processing or production, the method comprising: receiving an input image, converting the input image to a brightness and chrominance separated color space, identifying a highlight pixel region, and generating a highlight mask; expanding outwards by taking the boundary of the highlight mask as a reference, and constructing an annular analysis area; calculating a pixel gradient amplitude and a pixel gradient direction, and generating a linear structure feature data set; calculating a pixel color mean value and a pixel color standard deviation, and generating an abnormal region feature data set; performing defect distribution reasoning based on direction information in the linear structure feature data set and the abnormal region feature data set to generate a structure prior guidance graph; and carrying out source patch constraint according to the structure prior guidance graph, and processing the highlight pixel region to obtain an output image. According to the invention, the highlight removal process can be optimized, and the integrity of equipment defect features in the image is ensured.

In order to better predictively encode pixels of an image block of a video, a method of predicting a block of pixel colors of an image is proposed, comprising: determining a template-based intra mode to derive a prediction applicable to the block; determining a plurality of intra prediction modes, and determining respective costs for the plurality of intra prediction modes; determining that a first TIMD mode is a first intra prediction mode of the plurality of intra prediction modes having the lowest cost of the respective costs, and a second TIMD mode is a second intra prediction mode of the plurality of intra prediction modes having a penultimate cost of the respective costs; determining a third TIMD mode as a non-angular intra prediction mode; performing a verification with respect to the third TIMD mode being different from the first TIMD mode and the third TIMD mode being different from the second TIMD mode; forming a final TIMD mode based on the verification as true, the final TIMD mode comprising a linear combination of the first TIMD mode, the second TIMD mode, and the third TIMD mode; and forming a prediction of the block based on a template of the block and the final TIMD mode.

The application discloses a 4D video generation method fusing monocular vision and terrain elevation data, comprising the following steps: acquiring video frame images and corresponding camera pose data collected by a monocular camera; acquiring terrain elevation data of a target area, and constructing a three-dimensional elevation network model; based on the camera pose data, establishing a ray projection model for pixels in the video frame images, calculating the intersection of the rays and the three-dimensional grid model, and obtaining the reference distance from the monocular camera to the ground surface corresponding to the pixels; generating an initial relative depth map of the video frame images by using a depth estimation model; selecting high-confidence ground pixels from the video frame images as reference points, taking the reference distance corresponding to the reference points as the true value, and performing absolute scale correction on the initial relative depth map to obtain an absolute depth map; performing back projection calculation on the absolute depth map, the camera pose data and pixel color information to generate a three-dimensional point cloud, mapping the three-dimensional point cloud to a real geographic coordinate system, and generating 4D video data in time sequence.

The invention provides an intelligent graph recognition method and device based on collaborative drawing, equipment and a storage medium. The method is applied to the technical field of computers, and comprises the following steps: acquiring a canvas for collaborative drawing, performing pattern recognition processing on a pattern in the canvas for collaborative drawing, determining a boundary of the pattern, and performing segmentation processing on the pattern according to the boundary of the pattern to obtain at least one pattern and a pattern block corresponding to the pattern; the canvas for collaborative drawing is a drawing result obtained by collaborative drawing of a plurality of users; performing intelligent pattern recognition processing on the pattern block, and determining a visual component corresponding to a pattern in the pattern block; pixel point pickup processing is carried out on the graphic block, and each pixel point of the graphic block is traversed to obtain a pixel color value of the graphic block; and the data board is generated according to the visual component corresponding to the graph in the graph block and the pixel color value of the graph block, so that the identification accuracy is improved, and the development efficiency is improved.

The invention discloses a cloud rendering method and device based on a shared cache, equipment and a medium. Receiving a target scene identifier and a target scene view angle pose sent by the target terminal; loading a target scene model file according to the target scene identifier, and converting the target scene model file into a data structure object; loading a target radiance hash table corresponding to the target scene identifier from a public storage server; based on the target scene view angle pose and the target detection light, determining a patch intersection point set having a collision intersection point with patch data in the data structure object; and based on the target radiance hash table, determining a target radiance corresponding to each patch intersection point in the patch intersection point set, calculating a pixel color value of the corresponding patch intersection point in the patch intersection point set according to each target radiance, obtaining a target scene view angle image, and sending the target scene view angle image to a target terminal for display. Therefore, the data calculation amount of cloud rendering is reduced, and the cloud rendering efficiency in a multi-user scene is improved.

A pixel arrangement structure, a display panel, a display apparatus and a mask group are provided. The pixel arrangement structure includes basic pixel units in first and / or second directions. Each basic pixel unit includes five sub-pixels, first to third sub-pixels are of different colors, and third to fifth sub-pixels are of a same color; the first sub-pixel includes opposite first and second sides in the first direction, and opposite third and fourth sides in the second direction; and the second sub-pixel is on and separated from the third side of the first sub-pixel, the third sub-pixel is on and separated from the first side of the first sub-pixel, fourth and fifth sub-pixels are both on the fourth side of the first sub-pixel and are separated from the fourth side of the first sub-pixel, and are separated from each other in the first direction.

The invention belongs to the technical field of display, and particularly relates to a preparation method of a display panel and the display panel, and the preparation method of the display panel comprises the steps: providing a substrate, and forming an organic light-emitting unit on the substrate; forming a packaging layer on the organic light-emitting unit, wherein the packaging layer comprises a first inorganic layer, an organic layer, a heat insulation layer and a second inorganic layer which are stacked in sequence; forming a heating electrode on the second inorganic layer; forming a color filter layer on the heating electrode, wherein the color filter layer comprises a black matrix and a plurality of sub-pixel color resistors; and carrying out curing treatment on the color filter layer, namely electrifying the heating electrode to heat the heating electrode so as to provide heat required by curing. According to the invention, high-temperature curing of the color filter layer can be completed while the light-emitting unit is protected.

The invention provides a distortion and chromatic aberration combined pre-compensation method and system and MR head-mounted display equipment. The distortion and chromatic aberration joint pre-compensation method comprises the following steps: acquiring a first image to be compensated and gaze point information of a user; determining a first distortion compensation table about a first color and a first pixel color shift table of at least one second color relative to the first color according to the gaze point information; and respectively processing the first image according to the first distortion compensation table and each first pixel color offset table so as to obtain a second image which completes the joint pre-compensation. In this way, high-quality visual output can be achieved with low cost, and the optimal visual effect at different observation angles is achieved.

The application provides a method, device, equipment and medium for reducing image shooting requirements, and relates to the field of computer vision. The method comprises: collecting multi-view images of a scene to be rendered; sampling on a camera ray corresponding to a given pixel point to obtain a sampling point coordinate and a view direction; calculating a hour angle h, an declination δ' and a solar elevation angle θ s , a solar azimuth angle Φ s , obtaining a global light direction vector, and encoding; encoding the shooting time of the image; inputting the sampling point coordinate, the view direction, the light encoding and the time encoding into a neural network to obtain the color and the volume density of the sampling point under the corresponding view; obtaining the final predicted pixel color by using volume rendering, calculating the color loss; and updating the neural network parameters by back propagation. The application can weaken or even eliminate the influence of light changes on outdoor shooting, and reduce the shooting requirements of neural radiance field images.

The invention relates to an LCD (liquid crystal display) color enhancement method and related equipment, and the method comprises the following steps: collecting original color data of an LCD screen, and carrying out pixel-level division on the original color data to obtain a plurality of pixel color subsets; performing RGB color gamut mapping conversion on the pixel color subset to obtain a color gamut mapping subset, and performing color distribution statistics based on the color gamut mapping subset to obtain a color distribution histogram; when the proportional unbalance degree of the RGB three-channel components in the color distribution histogram exceeds a standard deviation range, performing color gain calculation on the original color data based on the color distribution histogram to obtain a color gain matrix; and color output adjustment is performed on a backlight unit of the LCD screen based on the color gain matrix to obtain an enhanced LCD display color, and the technical problem that local over-enhancement or color distortion is easily caused due to lack of dynamic perception and response to pixel-level color distribution characteristics of actual display content of the screen in a traditional color enhancement method is solved.

In a printing device, a print head performs printing based on image data. The image data represents an original image including a plurality of original pixels. The controller displays a preview image based on the image data. In the preview image, each preview-image pixel corresponds to one of the plurality of original pixels and has a color based on a color of the corresponding original pixel. The controller receives information on a preview-image pixel specified by a user. The controller sets an expanded region in the original image on the basis of a printing resolution. The expanded region includes original pixels having an original pixel corresponding to the specified preview pixel. The controller generates patch chart print data based on color values of original pixels in the expanded region. The controller controls the print head to print the patch chart image.

In one implementation, a method of rendering a scene including a portal is performed by a device including one or more processors and non-transitory memory. The method includes obtaining a rendering of first content having a plurality of first pixels at respective pixel locations having respective first pixel color values. The method includes obtaining a portal count map having a plurality of portal count pixels at the respective pixel locations having respective pixel portal count values indicating whether the corresponding pixel location corresponds to a portal. The method includes obtaining a rendering of second content having a plurality of second pixels at the respective pixel locations having respective second pixel color values. The method includes obtaining a portal cross map having a plurality of portal cross pixels at the respective pixel locations having respective pixel portal cross values indicating whether the corresponding pixel location corresponds to second content outside the portal. The method includes identifying an overwrite set of the respective pixel locations including pixel locations indicated by the portal count map as corresponding to the portal and including pixel locations indicated by the portal cross map as corresponding to the second content outside the portal. The method includes replacing the first pixel color values of pixels in the rendering of the first content at the overwrite set of the respective pixel locations with the corresponding second pixel color values.

The invention discloses a control method and device for narrowing the detection range of a tennis court and a storage medium, and relates to the technical field of image recognition, and the method comprises the steps: carrying out the dimension reduction processing and remodeling processing of an original image of the tennis court, and obtaining image data in a two-dimensional array form; pixel colors in the image data are clustered, and main colors corresponding to the tennis court are identified and screened out; after a binary mask is generated according to the main color, regularizing the binary mask according to a preset combination operation to obtain a target binary mask; analyzing the target binary mask by the connected domain, screening out a maximum connected region in the target binary mask, and generating a maximum connected region mask; and performing multi-direction projection processing on the maximum connected region mask, and determining a region of interest corresponding to the tennis court. Through the process of determining the region of interest, the problem that the detection effect of the tennis court is poor is solved, invalid calculation is reduced, interference is reduced, and the preprocessing efficiency and the positioning accuracy are improved.

The invention provides a document background interference removal method and device. The method comprises the steps of obtaining an original image in a to-be-processed document; performing pixel color clustering on the original image to obtain a plurality of color clusters; based on the original image and the plurality of color clusters, generating a mask image corresponding to each color cluster to obtain a plurality of mask images; and in response to a target mask image meeting a preset screening condition in the plurality of mask images, performing interference removal operation on the original image based on the target mask image to obtain a target image, thereby effectively improving the recognition accuracy of the document background interference, and significantly reducing the manual intervention demand and the error rate of subsequent processing.

The invention provides an unstructured grid volume rendering method and device based on a neural point field, and relates to the technical field of data processing, and the method comprises the steps: extracting an outer surface grid of a physical field domain from original unstructured grid data; adaptive sampling is carried out on the physical field space gradient modulus length, and a training data set containing sampling point coordinates and corresponding physical field values is obtained; training a pre-built neural point field model by adopting a strategy containing multi-scale Fourier feature coding; generating a projection light ray for each pixel of the image plane, determining a sampling range of the projection light ray in a physical field domain by using the outer surface grid, and generating a space sampling point in the sampling range; and inputting the spatial sampling points into the neural point field model to generate a predicted field value, and generating a corresponding pixel color. The invention provides an efficient solution for real-time and high-precision visual analysis of a large-scale unstructured grid physical field.

Saving power in an extended-reality device can include rendering a video stream on a display, tracking an eye of a user observing the display, ascertaining a gaze direction of the eye based on tracking the eye, calculating a foveal region of the display based on ascertaining the gaze direction in relation to the display, and modulating color hues of the video stream for pixels of the display outside the foveal region, to reduce a power consumption of the display. Modulating color hues is based on human color discrimination and display power consumption correlated to pixel color.

Embodiments described herein provide a 3D generation system from a single RGB image of an object by inferring the hidden 3D structure of objects based on 2D priors learnt by a generative model. Specifically, the 3D generation system may reconstruct the 3D structure of an object from an input of a single RGB image and optionally an associated depth estimate. For example, a radiance field is formulated to depict the input image in one viewpoint of the target 3D object, based on which other viewpoints of the 3D object can be inferred. Based on the visible surface depicted by the input image, points between the reference camera and the surface are assigned with zero density, and points on the surface are assigned with high density and color equal to the corresponding pixel in the input image.

The present disclosure relates to a system and method for improving or refining the accuracy and / or level of detail of a 3D surface based on pixel data from a set of images, such as color data of pixels. In particular, the present disclosure relates to a 3D scanner system comprising an intraoral 3D scanner, comprising: a projector unit comprising a light source and a pattern generating element for structuring light from the light source into a pattern to be projected onto a surface of an object; and two or more cameras configured to acquire a set of images, where the set of images includes images from each camera, where each image includes an array of pixels, each pixel having a pixel color; the scanner system further includes one or more processors operatively connected to the intraoral 3D scanner configured to: generate a three-dimensional (3D) surface of the object based on the set of images obtained from the camera, where the 3D surface includes a plurality of points and / or vertices; and generating a refined 3D surface by solving the optimization problem wherein points and / or vertices in the 3D surface are relocated such that for each point or vertex, a measure based on differences in pixel colors associated with that point or vertex will be minimized.

The application provides a color correction method, system, display device and chip, and relates to the technical field of display. The method comprises the following steps: converting initial color data of a pixel into initial coordinates in a target color space; the initial coordinates comprise components in each coordinate direction of the target color space; extracting binary high m bits of each component; extracting binary low n-m bits of each component; n is a pixel bit width; obtaining corrected color data of a plurality of sampling points corresponding to the pixel according to the high m bits; performing interpolation on the corrected color data of the plurality of sampling points according to the low n-m bits to obtain corrected color data of the pixel; each side length of the target color space is a maximum value of a pixel color range, the target color space is divided into a plurality of sampling cubes, vertices of the sampling cubes are sampling points, p is a number of the sampling points in a coordinate direction, and p=2 m +1.In the application, the pixel is displayed by using the corrected color data, so that the display screen can display a standard specified color gamut.

An image sensor includes a sensor substrate including a plurality of pixels configured to sense light; a color separation lens array including a plurality of pixel corresponding regions facing the plurality of pixels, wherein each pixel corresponding region of the plurality of pixel corresponding regions includes one or more nanoposts, and the one or more nanoposts are configured to form a phase profile that separates incident light for each wavelength, and to concentrate light in different wavelength bands on the plurality of pixels; and a filter array positioned between the sensor substrate and the color separation lens array, and including a plurality of transparent regions alternatingly arranged with a plurality of filters corresponding to a single color.

The present application relates to the field of botany and ecological measurement technology, and discloses a vegetation cover instrument calibration method and device, comprising: determining the position and area of the sample plot actually needed to be photographed, and taking a photo of the sample plot to obtain a sample plot photo; preprocessing the sample plot photo to obtain a processed photo; selecting several main vegetation colors in the processed photo as vegetation pixel colors, and selecting several main soil colors as soil pixel colors; setting a display screen; filling the display screen based on the selected vegetation pixel colors and soil pixel colors to form a training combination of the current color vegetation area ratio; comparing the similarity between the standardized vegetation map of the current color vegetation area ratio and the training combination to obtain a difference value; and calibrating the vegetation cover instrument based on the difference value. The present application can solve the problems of the existing vegetation cover instrument, such as the lack of measurement standards, large data deviation, and strong subjectivity of measurement results.

The application provides an image structured segmentation method, system, computer device and medium, and belongs to the field of image processing, comprising: obtaining an image to be segmented, and obtaining a preliminary segmentation result based on pixel color and spatial proximity; merging color blocks with color difference between adjacent color blocks less than a preset color merging threshold to obtain a preliminary merging result; at each scale, performing adjacent fusion on color blocks with color difference between adjacent color blocks in the image segmentation result at the previous scale less than a preset fusion threshold and the length of the circumscribed square less than the length of the circumscribed square threshold corresponding to the current scale to obtain the image segmentation result at the current scale, and determining the structured segmentation result of the image to be segmented according to the image segmentation results at multiple scales. The method can automatically generate and output a series of image segmentation results corresponding to different scale thresholds from fine granularity to coarse granularity, and realizes dynamic adjustment and on-demand selection of the segmentation granularity.

Data representing a 3D object to be rendered is obtained, the data comprising: a mesh structure defining 3D co-ordinates for each of a plurality of object vertices; and a feature vector encoding visual characteristics for at least one object surface defined by the plurality of object vertices. Motion information indicative of motion of the object in a scene is received. Based on the motion information, the mesh structure is deformed by adjusting the co-ordinates for one or more of the plurality of object vertices. The deformed mesh structure is processed using a graphics pipeline comprising a vertex shader and a fragment shader to generate a rendered image of the scene. The fragment shader comprises an artificial neural network trained to output pixel colour values for the at least one object surface on the basis of the visual characteristics encoded in the feature vector.

Pixel blending for neural network-based image generation is disclosed, specifically apparatuses, systems, and techniques for generating one or more images are presented. In at least one embodiment, two or more pixels from two or more images are blended based at least in part on a distance of the two or more pixels from a region of the two or more images, where the pixel colors are substantially similar.

Systems and methods for converting a raster image with a corresponding color scale into a plurality of vectors are provided. An example method includes receiving the raster image and the color scale. In some embodiments, the color scale includes a plurality of colors and a plurality of unit values. In certain embodiments, each color of the plurality of colors corresponds to a unit value of the plurality of unit values. In some embodiments, the raster image includes a plurality of pixels each corresponding to a pixel color. In certain embodiments, each color of the plurality of colors is segmented into a plurality of color channel values. In some embodiments, a model is trained to convert a color to a vector value based on the plurality of segmented color channel values for each color of the plurality of colors and the plurality of unit values. In certain embodiments, the plurality of vectors are generated and each include a vector location, a geometric shape, and a vector value.