37 results about "3D lookup table" patented technology

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.

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 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 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.

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.

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.

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.

The present disclosure relates to an image processing method, device, electronic equipment, chip and medium, wherein the method comprises: displaying a color coordinate system corresponding to a first color space; wherein the color coordinate system is used to indicate a first color coordinate of a first color value in the first color space; in response to a color adjusting operation on the color coordinate system, determining a second color coordinate of a second color value in the first color space; determining a color transformation relationship of a second color space according to a color transformation relationship between the first color coordinate and the second color coordinate, so as to perform color adjusting processing on an image in the second color space based on the color transformation relationship of the second color space; and determining a first three-dimensional lookup table according to the color transformation relationship of the second color space; wherein the color adjusting effect of the image can be intuitively displayed in the color coordinate system corresponding to the first color space, so that the color adjusting condition of the image can be understood in detail through the displayed color coordinate system, thereby improving the image processing efficiency.

The invention discloses a method for measuring the surface color of a special material, and the method comprises the steps: carrying out the color collection and analysis of the surface of the special material through an imaging scanning system; the method specifically comprises the following steps: inputting a model; fixing a to-be-detected sample on a translation mechanical platform; establishing a measurement coordinate system in an image detection host; defining a plurality of sampling areas in the image detection host; and performing global or local evaluation according to the color difference value. The method has the beneficial effects that the problems of efficiency and accuracy in high-glossiness and complex texture surface color measurement are effectively solved. The multi-angle arrangement and uniform illumination design of the light source overcome the mirror reflection interference, and the high-resolution imaging capability of the linear array scanning camera ensures the integrity of data acquisition. Accurate conversion from RGB to Lab is achieved through the 3D lookup table generated through deep learning, and the accuracy of color measurement is remarkably improved.

This invention discloses a real-time downconversion method for high dynamic range to standard dynamic range, comprising the following steps: S10, inputting an HDR video image into a static 3D lookup table (3DLUT) downconversion algorithm template, and outputting a first standard dynamic range (SDR) signal; S20, inputting the first SDR signal into an SDR image detection module to determine whether there is overexposure abnormality in the image after 3DLUT downconversion: if there is no overexposure abnormality, directly outputting the first SDR signal; if there is overexposure abnormality, correcting the 3DLUT mapping curve through a 3DLUT mapping curve adjustment module to complete the static 3DLUT parameter update; then, based on the updated static 3DLUT, regenerating the SDR signal through the static 3DLUT downconversion algorithm template, repeating the above detection and static 3DLUT parameter update process until the output SDR signal image has no overexposure abnormality.

The embodiment of the invention provides an image processing method, electronic equipment, a storage medium and a program product. The method comprises the following steps: acquiring a plurality of modal image data corresponding to a target area; performing feature extraction processing on the modal image data to obtain modal features corresponding to the modal image data; according to the modal features corresponding to the modal image data, determining an attention weight matrix corresponding to the target area, the attention weight matrix being used for indicating a fusion weight distribution proportion of the modal features; generating a target three-dimensional lookup table according to the attention weight matrix; and through the target three-dimensional lookup table, performing mapping processing on the multiple modal image data to generate a target image. The method is used for achieving the effect of improving the defect detection accuracy.

The invention discloses a land utilization type prediction method and system based on multi-source data fusion. The method comprises the steps of obtaining historical land utilization and multi-source driving factor raster data of a target area; a morphological adaptive transition probability is generated by coupling a deformable convolutional neural network; future land requirements are determined based on scene and policy coupling; a dynamic double-feedback cellular automaton model is adopted for iterative simulation, the model synchronously adjusts a competitive inertia coefficient and a spatial neighborhood weight, and spatial constraints such as an ecological protection red line are dynamically integrated through a three-dimensional lookup table; and finally, the prediction result is converted into standardized land coverage data through a probabilistic multilevel classification mapping engine, and a spatial uncertainty distribution diagram and an area confidence interval are synchronously generated. The deep internalization of the control rule is realized, complete decision support information containing uncertainty quantification is provided, and a scientific and reliable technical tool is provided for land space planning and management.

The embodiment of the invention discloses a color adjustment method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of display. The method comprises the following steps: acquiring an environment color temperature and a user color temperature; obtaining a plurality of three-dimensional lookup tables, wherein the plurality of three-dimensional lookup tables respectively correspond to different color temperatures; determining a first three-dimensional lookup table according to the similarity between the environment color temperature and the color temperature corresponding to each of the plurality of three-dimensional lookup tables; determining a second three-dimensional lookup table according to the similarity between the color temperature of the user and the color temperature corresponding to each of the plurality of three-dimensional lookup tables; and fusing the first three-dimensional lookup table and the second three-dimensional lookup table to obtain a target three-dimensional lookup table, and performing color adjustment based on the target three-dimensional lookup table. Therefore, the scheme can realize color temperature adjustment in combination with environment and user preference.

The application relates to a backlight white balance control method and device, electronic equipment and a storage medium. The method comprises the following steps: constructing a multi-temperature three-dimensional lookup table set; detecting the current working temperature of a backlight module when an image is displayed on a backlight display device, and determining the target light output characteristics of the current display picture; selecting a target three-dimensional lookup table from the multi-temperature three-dimensional lookup table set according to the current working temperature; inputting the target luminance value and the target chroma coordinate into the target three-dimensional lookup table to obtain a target three-color driving current value and generate a driving signal, and driving the backlight module to output mixed light matched with the target light output characteristics, so as to realize backlight white balance control. Based on the luminance, chroma and three-color driving current mapping relationship of the backlight, the mixed light meeting the target white balance requirement can be quickly and accurately output, the chroma coupling error caused by the traditional independent correction of the sub-channel is avoided, and the control precision and response speed of the backlight white balance are improved.

A device includes a memory circuit capable of storing a non-uniform 3-dimensional lookup table (3D LUT) specifying color correction data. For one or more of a red dimension, a green dimension, and a blue dimension, the non-uniform 3D LUT includes a number of color correction values within one or more first light ranges of the non-uniform 3D LUT that exceeds a number of color correction values included within one or more second light ranges of the non-uniform 3D LUT. The device includes a color correcting circuit capable of transforming a source frame into a color corrected frame using the non-uniform 3D LUT.

The application discloses an image conversion method and device, electronic equipment and a computer readable storage medium. The method comprises the following steps: obtaining a standard dynamic range image and a reference image thereof, and determining the RGB color value of the standard dynamic range image; calculating the internal feature correlation of the standard dynamic range image, and calculating the feature correlation between the standard dynamic range image and the reference image; obtaining the fusion feature correlation according to the internal feature correlation and the feature correlation, and determining the weight value of each three-dimensional lookup table according to the fusion feature correlation; searching for the initial RGB color value corresponding to the RGB color value in each three-dimensional lookup table, performing weighted calculation on the initial RGB color value and the weight value to obtain the target RGB color value; and generating the high dynamic range image corresponding to the standard dynamic range image by using the target RGB color value. The scheme can effectively improve the quality of the converted image in the conversion process from SDR data to HDR data, and guarantee the user experience.