49 results about "3D lookup table" patented technology

The invention provides a cross-platform content compatibility method and system based on a virtual shooting LED display screen. The method comprises the following steps: processing an irrelevant data content stream of a content stream of a heterogeneous content source to generate an intermediate data stream; constructing a virtual logic display space according to the resolution parameter of the intermediate data stream and the curvature data of the physical screen database; performing dynamic resource allocation based on the control point grid of the virtual logic display space, and generating a rendering task queue; loading a three-dimensional lookup table to perform forward color gamut conversion according to the rendering task queue and a physical screen color configuration file, and adjusting HSL offset according to collected real-time chroma data to generate frame cache data; and determining a delay compensation value based on the frame buffer data and the PTP clock signal, and inserting a corresponding time offset in an output queue through the delay compensation value to generate a multi-screen output signal. According to the scheme, the rendering accuracy, the color consistency and the display stability in the virtual shooting scene can be remarkably improved.

The invention relates to the technical field of vertical shaft guide detection, in particular to an industrial intelligent visual detection and diagnosis system for a vertical shaft guide. The coal dust shadow quantization unit extracts a coal dust region by adopting a double-peak self-adaptive threshold segmentation combined region growing algorithm, and introduces a space weight factor to calculate an average gray value and a coverage area proportion, and the dynamic coupling calibration unit depends on a three-dimensional lookup table calibrated by multiple working conditions and nonlinear interpolation; the optimal deviation compensation coefficient of the jitter and coal dust combination is matched, a dynamic gray segmentation threshold value is generated, and a defect diagnosis decision unit accurately calculates the abrasion depth through partition self-adaptive segmentation, multi-scale morphological filtering and denoising and gradient amplitude and curvature double-constrained sub-pixel edge detection. A hierarchical control instruction is output according to the real-time depth and the historical trend, coupling interference is eliminated, the cage guide abrasion detection accuracy is improved, and a reliable basis is provided for safe operation and maintenance.

The invention discloses a video color enhancement method and device based on deep learning guidance multi-lookup table fusion, equipment and a storage medium, and relates to the technical field of video enhancement, and the video color enhancement method based on deep learning guidance multi-lookup table fusion comprises the steps: obtaining a plurality of target three-dimensional lookup tables through an image classification network; obtaining a pixel adaptive weight through a sensing network; obtaining an initial pixel value of original video data, and determining a plurality of undetermined pixel values corresponding to the initial pixel value according to the plurality of target three-dimensional lookup tables; and processing the plurality of undetermined pixel values according to the pixel adaptive weights to obtain a target pixel value. According to the invention, the color hopping phenomenon between video frames after color enhancement can be reduced.

The invention relates to a color adjustment method and device, equipment and a medium. The method comprises the following steps: acquiring first lattice point data of each lattice point in an LAB color space; calculating a first color attribute of each grid point in the LAB color space based on the first grid point data of each grid point; adjusting the original saturation of each grid point based on a preset hue and saturation adjustment lookup table to obtain a first saturation; correcting the original hue of each lattice point to obtain a first hue of each lattice point; adjusting the first hue of each lattice point based on a preset hue and saturation adjustment lookup table to obtain a second hue; calculating second lattice point data of each lattice point in the LAB color space based on the first saturation and the second hue of each lattice point; and updating the initial three-dimensional lookup table based on the second lattice point data of each lattice point in the LAB color space. By adopting the method provided by the embodiment of the invention, the adjustment quality and the imaging effect can be improved.

This invention provides a method for extracting three-dimensional features of steel stamps on water transfer printing paper based on multispectral fusion, relating to the fields of optical inspection, machine vision, and automated quality control. This method utilizes adaptive illumination and image acquisition, employing optimal band optimization, polarization decoupling, and dynamic structured light projection to obtain a series of images separating geometric deformation and pattern interference. Three-dimensional reconstruction is performed using a physically constrained neural network, embedding a double-layer reflection optical model into the network to decouple and predict the paper substrate normal map and integrate to generate a high-precision three-dimensional point cloud. Multi-dimensional geometric features such as height, curvature, and shape are then extracted from the point cloud. Finally, based on a three-dimensional lookup table, the features are mapped to a comprehensive defect level, and automated, differentiated graded processing is performed. This invention achieves non-contact, micron-level high-precision inspection and intelligent quality control of steel stamps on complex surfaces.

The present application discloses an image color enhancement method, device and electronic device based on lookup table estimation, which relates to the field of video color enhancement. The method includes: using the feature extraction module of a preset color enhancement model to perform feature extraction on the image to be color enhanced, so as to obtain a pixel intensity feature image and a color feature image; using the lookup table weight estimation module of the preset color enhancement model to perform weight estimation on the pixel intensity feature image and the color feature image respectively, so as to obtain a pixel intensity lookup table weight corresponding to the pixel intensity feature image and an image color lookup table weight corresponding to the color feature image; performing calculation processing based on the pixel intensity lookup table weight, the image color lookup table weight and a preset initial 3D lookup table to obtain a target 3D lookup table; using the target 3D lookup table to perform color enhancement processing on the image to be color enhanced to obtain a target color enhanced image. The method of the present application can make the color enhancement result more stable and natural.

The application discloses a tone mapping method and system based on a lookup table and a Laplace filter, and belongs to the technical field of image processing.The input image is first decomposed into an adaptive Laplace pyramid;then a low-frequency image at the bottom layer of the adaptive Laplace pyramid is input into a weight predictor to obtain a pixel-level weight map, and a three-dimensional lookup table is used to perform three-linear interpolation on the low-frequency image to obtain a preliminary mapping image; then the preliminary mapping image and the weight map are fused pixel by pixel to generate an image at the bottom layer of the fine-tuned Laplace pyramid; then a filter parameter prediction module is used to learn a parameter value map of the remaining layer images of the adaptive Laplace pyramid, and the parameter value map is applied to a local Laplace filter to obtain the remaining layer images of the fine-tuned Laplace pyramid; finally, the fine-tuned Laplace pyramid is reconstructed to obtain a tone-mapped image.The application can retain local edge details of an image while performing global tone mapping.

The application is suitable for the technical field of image processing, and provides an image local color adjustment method and device, electronic equipment and storage medium, the method comprises the following steps: converting a first to-be-adjusted image obtained from an RGB color space to an HSL color space, adjusting the local color of the first to-be-adjusted image in the HSL color space, obtaining a calibrated HSL lookup table according to a plurality of sets of adjustment values obtained after adjustment, calibrating a preset three-dimensional lookup table based on the calibrated HSL lookup table to obtain a calibrated three-dimensional lookup table, and adjusting the color of a second to-be-adjusted image according to the calibrated three-dimensional lookup table, so that the local color of the image is adjusted, and the quality of the whole image is improved.

The application discloses a three-dimensional look-up table (3D-LUT) construction method and a color correction method based on FPGA, wherein the construction method comprises: interval sampling a 3D-LUT from three dimensions to form a three-dimensional look-up table, and the three-dimensional look-up table comprises: eight Sub-LUTs for storing split 3D-LUT data; wherein N is the sampling point number of three RGB channels in the 3D-LUT; the 3D-LUT contains (N-1) 3 cubic units; the Sub-LUT contains (M-1) 3 cubic units; and M is the sampling point number of three RGB channels in the Sub-LUT. The method can reduce BRAM resource occupation and is suitable for the technical field of image and video processing.

The invention provides a display panel Demura compensation method and system based on three-dimensional lookup table iteration, and the method employs an iteration strategy to optimize compensation data based on a photographing device and a lookup table compensation scheme so as to gradually approach an optimal solution or meet specific requirements. According to the method, the problem of insufficient single compensation effect is solved, optimization can be carried out according to specific characteristics of different display panels, and the method has high universality and wide expansion potential. The method breaks through the limitation of the prior art, is not limited by a specific application type, and can maintain excellent performance and effect on different types of display panels.

The present disclosure provides a data mapping method based on a three-dimensional lookup table, comprising: acquiring an original grayscale value of a target pixel point and the color depth of the target pixel point, and shifting the original grayscale value left by a predetermined number of bits to obtain a target grayscale value; performing first mapping processing on the target grayscale value to obtain a mapped grayscale value; establishing a source cube containing the target pixel point, and acquiring the position of the target pixel point in the source cube to obtain first coordinates; expanding the source cube to obtain a target cube, and acquiring the position of the target pixel point in the target cube to obtain second coordinates; on the basis of the second coordinates, determining a target tetrahedron containing the second coordinates in the target cube, and on the basis of the target tetrahedron, performing second mapping processing on the second coordinates to obtain third coordinates; and performing interpolation processing on the third coordinates to obtain a target mapped value of the target pixel point. The method solves the problem in the prior art of low data mapping precision of a data mapping method.

Provided in the embodiments of the present application are a three-dimensional lookup table construction method, an image processing method, a computer program product, a device, and a storage medium. During construction of a three-dimensional lookup table for correcting an initial color in an image into a target color, with respect to different target sampling points needing color correction amongst a plurality of sampling points, adjustment values of the target sampling points in a certain channel can be obtained by adjusting the difference value between a channel value of the target color and a channel value of the initial color in the channel by using different adjustment amplitudes, wherein the adjustment amplitudes of the different target sampling points in a certain channel can be determined on the basis of the proximity between the channel values of the target sampling points and the channel value of the target color in the channel, and / or determined on the basis of the channel values of the target sampling points in the channel. In this way, more accurate and refined three-dimensional lookup tables can be constructed, so as to perform more precise color correction on target images, thereby reducing color banding in corrected images.

The present application relates to the vertical shaft cage detection technical field, specifically, it relates to a kind of industrial intelligent vision detection and diagnosis system for vertical shaft cage, acquisition unit synchronously obtains cage flange surface image and cage car pitch angle, coal dust shadow quantization unit uses bimodal adaptive threshold segmentation combined with region growing algorithm to extract coal dust area, introduce space weight factor to calculate average gray value and coverage area proportion, dynamic coupling calibration unit relies on three-dimensional look-up table and nonlinear interpolation of multi-working condition calibration, match the optimal deviation compensation coefficient of the combination of jitter and coal dust, generate dynamic gray scale segmentation threshold, defect diagnosis decision unit is through zoned adaptive segmentation, multiscale morphological filtering denoising, combined with gradient amplitude and curvature double-constraint subpixel edge detection accurately calculate wear depth, according to real-time depth and historical trend output grading control instruction, eliminate coupling interference, improve cage wear detection accuracy, provide reliable basis for safe operation.

The application discloses an image processing method and device and a training method, relates to the field of image processing, and particularly relates to the fields of computer vision, deep learning and artificial intelligence. The specific implementation scheme is as follows: for each pixel point in a to-be-processed image, according to a first color value of the pixel point, a voxel index of the pixel point in a three-dimensional lookup table and a relative coordinate of the pixel point in a target voxel corresponding to the voxel index are determined; according to the voxel index, first color information of each vertex of the target voxel is acquired; a weight generation model obtained by joint training of the three-dimensional lookup table is used to determine a first weight of the vertex according to the relative coordinate; according to the first color information and the first weight, second color information of the pixel point after color mapping is determined; and a target image is generated according to the second color information of each pixel point.

The invention relates to an image processing method and device, electronic equipment, a chip and a medium, and the method comprises the steps: displaying a color coordinate system corresponding to a first color space; wherein the color coordinate system is used for indicating a first color coordinate of a first color value in the first color space; in response to a toning operation on the color coordinate system, determining a second color coordinate of a second color value in the first color space; according to the color transformation relation between the first color coordinate and the second color coordinate, determining the color transformation relation of the second color space, and carrying out toning processing on the image in the second color space based on the color transformation relation of the second color space; determining a first three-dimensional lookup table according to the color transformation relation of the second color space; wherein the color matching effect of the image can be visually displayed in the color coordinate system corresponding to the first color space, so that the color matching condition of the image can be known in detail through the displayed color coordinate system, and the image processing efficiency is improved.

Systems, apparatuses, and methods for reducing three dimensional (3D) lookup table (LUT) interpolation error while minimizing on-chip storage are disclosed. A processor generates a plurality of mappings from a first gamut to a second gamut at locations interspersed throughout a 3D representation of the pixel component space. For example, in one implementation, the processor calculates mappings for 17×17×17 vertices within the 3D representation. Other implementations can include other numbers of vertices. Rather than increasing the number of vertices to reduce interpolation error, the processor calculates mappings for centroids of the sub-cubes defined by the vertices within the 3D representation of the first gamut. This results in a smaller increase to the LUT size as compared to increasing the number of vertices. The centroid mappings are used for performing tetrahedral interpolation to map source pixels in the first gamut into the second gamut with a reduced amount of interpolation error.

The application discloses a land use type prediction method and system based on multi-source data fusion, and the method comprises the following steps: acquiring historical land use and multi-source driving factor grid data of a target region; generating a shape self-adaptive conversion probability through a neural network coupled with deformable convolution; determining future land demand based on scenario and policy coupling; iteratively simulating by using a dynamic double feedback cellular automaton model, the model synchronously adjusts the competition inertia coefficient and the spatial neighborhood weight, and dynamically integrates spatial constraints such as ecological protection red lines in a three-dimensional lookup table; finally, the prediction result is converted into standardized land cover data through a probabilistic multi-level classification mapping engine, and a spatial uncertainty distribution map and an area confidence interval are synchronously generated. The method realizes the deep internalization of regulatory rules, provides complete decision support information containing uncertainty quantification, and provides a scientific and reliable technical tool for land space planning and management.

The invention provides a gene data lookup table coding method and device based on in-memory calculation. The method comprises the following steps: splitting three-dimensional lookup table data, and sequentially storing the split three-dimensional lookup table data into a plurality of SRAM (Static Random Access Memory) arrays; the method comprises the following steps: acquiring an input sequence of gene data with the length of L, and arranging the input sequence into L-2 triads (addr1, addr2, sym) according to the position of a symbol in the input sequence; determining a target array from the plurality of SRAM arrays according to addr1 in the triads, transmitting N triads to the target array of the triads at a time, and determining a to-be-searched data row from all data rows of the target array according to addr2 in the triads; three dimensions of the lookup table respectively correspond to three dimensions of an addr1 one-dimensional array, an addr2 one-dimensional array and a sym one-dimensional array; the target array completes comparison between all symbols of a data row to be searched and sym in the triple in a single period through a single-period byte search operation, and outputs a comparison result vector; and recording positions representing that the comparison results are the same in the comparison result vector to an output buffer area of the target array, and replacing symbols sym of the input sequence with the positions.

The image processing method includes: displaying a first screen, where the first screen includes a first control; detecting a first operation on the first control; determining a first mapping in a three-dimensional lookup table in response to the first operation, where the first mapping is corresponding to the first control; converting a to-be-processed image in a first color space into a first image in a second color space, where the to-be-processed image is an image obtained in the first color space; processing the first image according to the first mapping to obtain a second image; and converting the second image in the second color space into a third image in the first color space.

According to the construction method and color correction method of the three-dimensional lookup table based on the FPGA, the construction method comprises the steps that interval sampling is conducted on 3D-LUT from three dimensions to form the three-dimensional lookup table, and the three-dimensional lookup table comprises eight Sub-LUTs used for storing split 3D-LUT data; wherein N is the number of sampling points of RGB (Red, Green, Blue) channels in the 3D-LUT; the 3D-LUT comprises (N-1) 3 cubic units, and (N-1) < 3 > cubic units are included in the 3D-LUT; the Sub-LUT comprises (M-1) three cubic units, and the number of the cubic units is (M-1); m is the number of sampling points of RGB channels in the Sub-LUT; the method can reduce the occupation of BRAM resources, and is suitable for the technical field of image and video processing.

The present invention discloses a method and device for image harmonization processing, which can improve the expressiveness of a 3D lookup table while occupying fewer memory and computer resources. The method comprises: extracting features from a composite image to be processed to obtain composite features; utilizing the composite features to determine the weights of each subnetwork in a trained three-dimensional lookup table network, wherein the three-dimensional lookup table network is obtained by training an initial three-dimensional lookup table network using a training composite image as input and a training original image corresponding to the training composite image as output; determining a prediction network in the three-dimensional lookup table network based on the subnetworks and their weights; and harmonizing the composite image based on the prediction network to obtain a harmonized image of the composite image.

The application discloses a display method and electronic equipment, the method comprises the following steps: at a first time point, a video channel module in a DPU channel acquires data of a first video from an HDR video frame; then a three-dimensional lookup table module processes the data of the first video to obtain a first picture of the first video, and the first picture is displayed through a first display module; at the same time, the CPU can store the three-dimensional lookup table in the DPU channel. At a second time point, in response to displaying a first window in a display interface of the first video, the CPU converts the three-dimensional lookup table into a two-dimensional image and transmits the two-dimensional image to a GPU channel. The data of the first video is processed through a restoration module and a three-dimensional mapping module in the GPU channel to obtain a second picture of the first video, and the second picture is displayed through a second display module. Through the application, the problem of brightness jump of a video picture can be avoided, and the visual effect is ensured.

A method includes obtaining an image and a gain map associated with the image. The method also includes identifying image patches in the image and corresponding gain map patches in the gain map. Different image patches are centered around different anchor points in the image. The method further includes, for each image patch and its corresponding gain map patch, generating an intensity-gain curve for the associated anchor point. The intensity-gain curve specifies (i) gain values based on the corresponding gain map patch for intensity values up to a threshold intensity value and (ii) gain values based on one or more input parameters for intensity values above the threshold intensity value. In addition, the method includes combining the intensity-gain curves to generate a 3D lookup table, which identifies the gain values for the anchor points in the image at each of multiple intensity values.

The present disclosure provides a method for generating a screen color calibration file and a screen color calibration method, and relates to the field of screen color calibration under multiple luminances. The method comprises the following steps: determining a color coordinate matrix of three primary colors corresponding to the screen under N luminances, wherein N is a positive integer greater than 2; determining a conversion function matrix corresponding to the screen according to the N color coordinate matrices, wherein the conversion function matrix is used to map the color gamut of the screen under each luminance to the color gamut under a reference luminance; performing color calibration on the screen under the reference luminance to obtain a three-dimensional lookup table under the reference luminance; and determining the conversion function matrix and the three-dimensional lookup table as the color calibration file of the screen. Thus, the color gamut under different luminances can be kept consistent, and color calibration under the maximum luminance can ensure the color accuracy under all luminances, thereby ensuring the reliability of screen color calibration and improving the calibration efficiency.

The invention relates to a display device and an image bright color enhancement method. A display device includes a display and a controller. Wherein the display is configured to display a user interface; the controller is configured to: a display configured to display an image and / or a user interface; the controller is configured to convert the down-sampling RGB image to obtain an ICtCp image; inputting the ICtCp image into a first convolutional neural network, and outputting a one-dimensional lookup table of a brightness component I and a two-dimensional lookup table of a chrominance component CtCp; performing ICtCp color space inverse conversion to generate a first RGB three-dimensional lookup table; fixing network parameters of the first convolutional neural network, and inputting the downsampling RGB image into a second convolutional neural network to generate a residual RGB three-dimensional lookup table; and according to the first RGB three-dimensional lookup table and the residual RGB three-dimensional lookup table, performing lookup mapping operation on the original RGB image to generate a target RGB image. By adopting the method, the accuracy and computing power requirements are considered, so that the computing power of the television end can be better adapted.

An apparatus includes an acquisition unit configured to acquire a pair of first data and second data, the first data being obtained by imaging an object under a first environment, the second data being obtained by imaging the object under a second environment, and a processing unit configured to generate a three-dimensional lookup table by using the pair of the first data and the second data, the three-dimensional lookup table holding a condition for image processing to convert the first data into the second data.

In an example method, for a plurality of octants, residual information is obtained for one or more vertices of the respective octant, where the vertices correspond to respective points in a three-dimensional lookup table. The lookup table is decoded recursively as follows: at least a first one of the plurality of octants is decoded by reconstructing at least a first color sample value from the residual information for at least a first vertex of the first octant; and a plurality of second octants in the plurality of octants are decoded, where the second octants are obtained by splitting the first octant. A color transform is then applied based on the decoded lookup table.

This application discloses a method, apparatus, and electronic device for reconstructing a three-dimensional lookup table, belonging to the field of image processing technology. The method includes: acquiring a base image dataset and a target image dataset; wherein the matching degree of image content between any base image in the base image dataset and the corresponding target image in the target image dataset is greater than a preset threshold; performing three-dimensional point cloud registration on the base image dataset and the target image dataset to obtain a mapping relationship between the pixels of the base images in the base image dataset and the pixels of the target images in the target image dataset; and reconstructing an initial three-dimensional lookup table based on the mapping relationship to obtain a target three-dimensional lookup table.

According to the drawing assisting system and method based on intelligent composition, personalized and dynamic drawing assisting is achieved through cooperation of multiple modules, the stroke position, pressure and speed are monitored in real time, composition complexity and a pressure thermodynamic diagram are calculated, a user concerned area is marked, the user stroke is compared with an art rule base, a three-dimensional lookup table is established, and the drawing assisting effect is achieved. The method comprises the following steps: storing user preferences, historical analysis and general rule coefficients, dynamically switching a local lightweight AI and a cloud deep optimization model, identifying a creation environment through multi-sensor fusion, calculating a fatigue index in combination with stroke pressure, speed and path curvature, providing strength adjustment suggestions, and storing user data by adopting a time sequence database. Through K-means clustering and LSTM behavior prediction, a model is updated in a weekly incremental manner, preference changes are captured, suggestions are optimized through testing, and through multi-dimensional data fusion, dynamic model adaptation and user behavior learning, creation efficiency and an artistic effect are remarkably improved.

The invention relates to the technical field of pipeline measurement, and discloses a three-dimensional prior pipe diameter extraction method and electronic equipment, and the method comprises the steps: obtaining multi-physics field coupling data; constructing a three-dimensional lookup table based on materials, dielectric constants and conductivity; inquiring the velocity initial value of the electromagnetic wave and the pipeline estimated depth value from the three-dimensional lookup table, adopting adaptive edge detection and picking up the vertex and edge feature points of the hyperbolic curve of the pipeline at a sub-pixel level, and outputting a confidence label; taking the vertex, the edge feature point and the confidence label as input, and calculating an initial circle center and a radius of the pipeline by utilizing sub-pixel-level scattering point inversion; and performing triple weighted voting and sub-pixel peak value optimization on the initial circle center and radius by utilizing triple weighted Hough circle detection to obtain the circle center and coordinates of the pipeline, and controlling the pipe diameter identification error and improving the pipe diameter precision by depending on the three-dimensional lookup table based on the material, the dielectric constant and the conductivity and combining the sub-pixel-level scattering point inversion and the triple weighted Hough circle detection.