31 results about "Pixel value difference" patented technology

Disclosed is a method for enabling exposure-guided three-dimensional (3D) reconstruction, including (i) receiving Low Dynamic Range (LDR) input image captured by camera; (ii) rendering High Dynamic Range (HDR) image corresponding to input image, using HDR 3D reconstruction model pre-trained for HDR image reconstruction of 3D environment; (iii) applying HDR to LDR tone-mapping operator on HDR image, for producing tone-mapped LDR image; (iv) determining first loss function (FLF) between input image and tone-mapped LDR image, FLF comprising weighted pixel value differences between pixels of input image and corresponding pixels of tone-mapped LDR image; (v) determining whether input image has saturated pixel(s), saturated pixel(s) comprises: highlight saturated pixel, shadow saturated pixel; (vi) de-weighting pixel value difference corresponding to saturated pixel in FLF; (vii) back-propagating gradient of FLF with respect to model parameters, through differentiable render function of HDR 3D reconstruction model, for adjusting model parameters in way that reduces FLF.

The invention discloses a full-process visual monitoring and intelligent management method for a glass bracket production line, and relates to the technical field of industrial quality control, and the method comprises the steps: carrying out the continuous image collection of all stations of the glass bracket production line through an image collection unit, and constructing a full-process image data sequence; detecting the size of the glass bracket by using the qualified glass bracket size image database, and judging whether the size is abnormal or not; further performing defect detection on the glass bracket with the normal size, and determining whether an abnormal defect exists or not through pixel value difference analysis; and finally, summarizing the glass brackets with abnormal sizes or defects and related information thereof, and generating a visual quality report, so as to quickly position problems and optimize the production process. The comprehensive monitoring and intelligent management of the glass bracket production process are realized, and the production efficiency and the product quality are improved.

The application relates to the field of infrared thermal imaging technology, and particularly provides an infrared thermal imaging AI intelligent temperature measurement method.The method comprises the following steps: image input and preprocessing, receiving infrared images and sunlight images photographed by an infrared thermal imager, classifying based on pixel value differences, and preprocessing to obtain binary images; image cutting, cutting the binary images, and identifying the boundaries of numbers and symbols; characteristic value calculation and extraction, dividing regions according to the boundaries of the numbers and symbols, and performing feature extraction to construct a characteristic vector; number classification and identification, comparing the characteristic vector with a pre-trained K-nearest neighbor algorithm (KNN) model to identify the numbers and symbols; and image number output, combining the identified numbers and symbols into complete temperature values, outputting the identification result, and storing the identification result for comparison diagnosis.The method automatically and accurately identifies temperature information in the infrared images, and realizes intelligent comparison diagnosis.

The invention discloses a video frame rendering method, system and device, a storage medium and a program product, and belongs to the technical field of video processing. And a decoder in the CPU transmits the reference frame data to a reference frame cache region of the GPU. And a graph renderer in the GPU renders the reference frame according to the reference frame data. And a decoder in the CPU generates residual data according to the pixel value difference between the target frame and the reference frame, and transmits the residual data to a residual cache region of the GPU. And a graphic renderer in the GPU renders a local image area of the target frame according to the residual data, and superposes the local image area of the target frame with the reference frame to obtain a rendered image of the target frame. The technical effects of reducing GPU computing resources and memory bandwidth consumption, reducing data transmission delay and improving rendering efficiency and resource utilization rate in a high-resolution and high-frame-rate scene are achieved.

The invention provides a radiomics feature extraction and analysis method for a liver cancer CT image, and the method comprises the steps: obtaining a multi-time-phase computed tomography image sequence, extracting contrast agent concentration distribution data of each time phase from the sequence, and obtaining a concentration change rate sequence through pixel value difference calculation; for the rapid change stage, applying a feature extraction algorithm to obtain high-density texture features from the image data of the stage, and obtaining quantitative description of subtle instantaneous change; determining the distribution position and intensity of the abnormal texture in the rapid change stage through the quantitative description, and generating an abnormal texture distribution diagram; and according to the abnormal texture distribution diagram and the overall trend summarization sequence, fusing the abnormal texture distribution diagram and the overall trend summarization sequence to generate a comprehensive dynamic change model, and determining an adjustment parameter of the analysis fineness degree of each stage.

The application discloses a kind of based on optimization's guiding filter image fusion change detection method and device, method includes: by extreme minimum scale difference operator, pixel value difference value is to the picture of same scene different phase, obtains difference map;Using the way of guiding filter, difference map is fused on global scale, to obtain the optimal difference map;Mean filter is used to phase map I1 and I2, and the base layer difference map corresponding to each difference map is obtained, and the optimized brightness saliency map F1 and F2 are obtained by pca fusion as the image of generating saliency map, according to the principle of maximum saliency to determine weight map;Weight map is regularized for double-scale difference map reconstruction, and the final difference map is obtained;In clustering segmentation stage, by introducing soft threshold function, the final difference map is further processed, to suppress existing abnormal noise.The device includes: processor and memory.

The invention discloses an intelligent cloth printing defect monitoring method and system based on machine vision, and relates to the field of image data processing, and the method comprises the steps: collecting a real-time video stream on the surface of a fabric, intercepting single-frame image data, and carrying out the grid segmentation, so as to obtain candidate image blocks; performing feature clustering analysis on sample blocks in the candidate image blocks, and constructing a standard texture feature library; sparse coding operation is carried out on the candidate image blocks based on the standard texture feature library, linear combination weights are solved, and sparse coefficients are obtained; generating a reconstructed image block according to the standard texture feature library and the sparse coefficient; calculating a pixel value difference between the candidate image block and the reconstructed image block to obtain a residual matrix representing a difference degree; and when the energy norm value of the residual matrix is greater than an anomaly judgment threshold value, outputting a marking signal indicating that the corresponding candidate image block has an image defect. By implementing the method and the device, defect detection without a preset template can be realized, and the adaptability of printing defect monitoring is improved.

The application discloses a pattern defect detection method and device and a storage medium. The method comprises the following steps: obtaining an overall pattern region and a plurality of local pattern regions corresponding to a target pattern in a to-be-detected image, and obtaining an overall template image and a plurality of local template images from template information corresponding to the target pattern; aligning the overall pattern region with the overall template image, and respectively aligning each local pattern region with a corresponding local template image; determining a first defect position in the overall pattern region based on a first pixel value difference between the aligned overall pattern region and the overall template image, and respectively determining a second defect position in each local pattern region based on a second pixel value difference between the aligned each local pattern region and the corresponding local template image; and comprehensively determining a third defect position of the target pattern in the to-be-detected image based on the first defect position and the second defect positions. Through the above method, the accuracy of pattern defect detection can be improved.

The application discloses a lossless compression method and system for image sensor raw data, and relates to the technical field of image sensors.The application fully utilizes the statistical characteristics that the pixel value difference between adjacent frames under the same exposure is extremely small, combines the inherent color arrangement rule of the Bayer format image, separates the color channels first and then performs time domain difference calculation, greatly reduces the data entropy value, and obtains a compression ratio much higher than that of a general lossless compression algorithm on the premise of completely lossless original pixel values; meanwhile, independent compression and packaging are performed with the minimum service unit as the granularity, target data can be directly located and accessed without decompression and large-scale package, the data retrieval and calculation overheads are reduced, the traceability of the original data is retained, the statistical confidence of the test result is not affected, and the batch data storage requirement in the image sensor production test scene is adapted.

An object of the present invention is to solve the problems of the prior art, that is, to provide a method for determining the quality of a placing joint surface treatment, which can objectively determine the quality of the placing joint surface treatment after estimating the distribution state of aggregates on a concrete surface.SOLUTION: The construction joint surface processing determination method is a method for determining the quality of construction joint surface processing on the basis of an original image obtained by photographing a concrete surface, and includes an original image acquisition process and an aggregate extraction process. In the original image acquisition step, a first smoothed image and a second smoothed image are generated by smoothing an original image. In the aggregate extraction step, a portion where a pixel value difference between the first smoothed image and the second smoothed image exceeds an aggregate threshold value is extracted as an aggregate portion. To determine the quality of placing joint surface processing on the basis of the ratio of an aggregate part occupying an object area corresponding to an original image.SELECTED DRAWING: Figure 3

A thermal image processing method according to the present invention comprises the steps of: receiving a captured image from a thermal image camera; dividing each frame included in the captured image into a plurality of blocks; identifying each block as a target block or an excluded block on the basis of the pixel value difference between corresponding blocks of two neighboring frames and / or the average pixel value of each block of the frame; determining whether to mark each block position on the basis of the cumulative count of the target block within a plurality of frames; calculating a non-uniformity correction value for an unmarked block position; and outputting a corrected image by correcting the captured image on the basis of the calculated non-uniformity correction value.

The application relates to a defect identification method, device and computer equipment, which comprises the following steps: acquiring an image containing a power small fitting collected by an image collection device; determining a depth threshold according to an actual shooting distance of the image; wherein the actual shooting distance is the actual distance between the image collection device and the power small fitting, and the depth threshold is positively correlated with the actual shooting distance; extracting a region of interest containing the power small fitting from the image according to the depth threshold; determining the definition of the region of interest according to the pixel value difference of different pixel points in the region of interest; and performing defect identification of the power small fitting according to the region of interest and the definition when the definition is greater than a preset definition threshold. The application can improve the accuracy and efficiency of image screening to ensure the accuracy and efficiency of defect identification.

The invention discloses an image magnification method, an image magnification device, an image processing chip and display equipment. The method comprises the following steps: receiving an original image; carrying out edge detection on the original image and calculating a pixel value difference value in the original image; judging whether the pixel value difference value is greater than a preset threshold value or not; when the pixel value difference value is greater than a preset threshold value, amplifying the original image by adopting a first interpolation method; and when the pixel value difference value is not greater than a preset threshold value, amplifying the original image by adopting a second interpolation method. According to the image magnification method, the image magnification device, the image processing chip and the display equipment provided by the invention, the edge part of the image is detected, and different magnification algorithms are selected according to the pixel value difference, so that the display effect of a color image is reserved, and the sharpness of images such as an image engineering drawing and fonts after magnification is enhanced.

In the present invention, an information processing device is capable of generating sub-images to be sequentially displayed, and comprises: a first processing unit that, on the basis of a frame image, is capable of generating two or more sub-images among a plurality of sub-images having a plurality of pixel values and arranged in a predetermined arrangement pattern in the frame image; a detection unit that detects detection pixels to be processed, on the basis of the display order of corresponding pixels of the two or more sub-images and the pixel value difference between the pixels in the display order and on the basis of the coordinates of the frame image; and a second processing unit that executes processing for reducing the pixel value difference between corresponding pixels in the detection pixels.

The application provides an image frame encoding method and device, a chip, electronic equipment, a storage medium and a computer program product, and relates to the field of image processing. The method comprises the following steps: obtaining a current image frame, the current image frame comprising a first image frame and a second image frame, the first image frame being a previous image frame of the current image frame, the second image frame being a previous image frame of the first image frame, and the current image frame being an image frame in a video stream that needs to be transmitted from a first node to a second node; determining a current predicted image frame according to the first image frame and the second image frame; determining a residual image between the current image frame and the current predicted image frame; determining a plurality of first image blocks with pixel value differences between the current image frame and the first image frame; in a case where the number of the first image blocks is less than or equal to a preset number, losslessly compressing image blocks in the residual image that are located at the same positions as the plurality of first image blocks; and transmitting the losslessly compressed image blocks to the second node.

The present application relates to the technical field of laser cutting, and particularly relates to a sheet metal laser cutting device and a laser cutting method thereof. The present application selects a piercing point of an outline and starts cutting at the piercing point; according to the pixel value difference of the corresponding pixel points in the sheet metal infrared image of the start and end time of the starting cutting point of the cutting crack in the local time period, the position and pixel value of the pixel points on the cutting crack, and the cutting position and the cutting crack width, the heat response position optimization degree is obtained; according to the relative size of the piercing optimization degree of the pixel points on the cutting crack of each local time period and the previous local time period of each outline, and the heat response position optimization degree of the previous local time period, the pulse demand degree is obtained, and then the actual pulse frequency of the previous local time period is adjusted, the preferred pulse frequency of each local time period is obtained, and the cutting of each outline is completed. The present application adaptively determines the preferred pulse frequency of the local time period of each outline, and improves the sheet metal laser cutting precision.

This invention discloses an underwater image collaborative enhancement and super-resolution method, belonging to the field of computer vision technology. It includes constructing a training dataset for the model training process using an underwater image dataset with visual enhancement reference images. The training dataset includes low-resolution original underwater degraded images, low-resolution reference ground truth images, high-resolution original degraded underwater images, and high-resolution reference ground truth images. An underwater image collaborative enhancement and super-resolution deep learning network is constructed, using pairs of original underwater degraded images as input to the deep network, and using their corresponding low-resolution reference ground truth images to constrain and optimize the predicted images output by the model. The model training process is constrained and optimized by minimizing pixel value difference loss and structural similarity loss, thereby training the underwater image collaborative enhancement and super-resolution deep learning network. Any pair of original underwater degraded images is used as input to the model, and the output is obtained through model calculation.

Disclosed is a method for enabling exposure-guided three-dimensional (3D) reconstruction, including (i) receiving Low Dynamic Range (LDR) input image captured by camera; (ii) rendering High Dynamic Range (HDR) image corresponding to input image, using HDR 3D reconstruction model pre-trained for HDR image reconstruction of 3D environment; (iii) applying HDR to LDR tone-mapping operator on HDR image, for producing tone-mapped LDR image; (iv) determining first loss function (FLF) between input image and tone-mapped LDR image, FLF comprising weighted pixel value differences between pixels of input image and corresponding pixels of tone-mapped LDR image; (v) determining whether input image has saturated pixel(s), saturated pixel(s) comprises: highlight saturated pixel, shadow saturated pixel; (vi) de-weighting pixel value difference corresponding to saturated pixel in FLF; (vii) back-propagating gradient of FLF with respect to model parameters, through differentiable render function of HDR 3D reconstruction model, for adjusting model parameters in way that reduces FLF.

An image inputter and a controller are provided, and the controller acquires a multiple-value image via the image inputter, acquires a first image obtained by performing a correction process and a simple binarization process on the multiple-value image and a second image obtained by performing the correction process on the multiple-value image, uses a difference value of a pixel value of the second image with respect to the first image on a pixel-by-pixel basis to determine whether a jaggy occurs when the multiple-value image is output as a simple binary image, when a jaggy occurs, determines a conversion method for converting the multiple-value image in accordance with an amount of statistics calculated using the difference value, and outputs an image obtained by conversion using the determined conversion method.

The application discloses a pupil positioning method and device, which establishes M vectors for the to-be-processed pixels of an image, the M vectors correspond to different angles, and the vectors represent the pixel value difference between L pixels at the angle corresponding to the vector of the current pixel and the current pixel; for the pixels in a preset image region, an accumulated vector of the M vectors of the current pixel is obtained, a direction interval to which the accumulated vector of the current pixel belongs is determined, the average position of the pixels in the preset image region whose accumulated vectors belong to the same direction interval is obtained, and a mapping vector of any direction interval is established with the preset position and the average position as end points; and whether the preset image region corresponds to a pupil is determined according to the uniformity of the distribution of the mapping vectors. According to the application, the vectors reflecting the pixel value difference between the pixels and the surrounding pixels of the image are established according to the pixel values of the image, the direction interval distribution of the vectors in the image region is determined, and whether the image region corresponds to a pupil is determined, so that the pupil can be positioned more accurately under various complex conditions.

The application relates to the technical field of image processing, in particular to a circuit etching method and device for a thermal printing sheet, which comprises the following steps: obtaining each structure region in an exposure image of the thermal printing sheet; obtaining pixel disorder degrees of each structure region by equally dividing all pixel values in each structure region and analyzing pixel step changes and pixel value differences in the region; and obtaining an angle point distribution difference degree of each structure region by using angle point features in each structure region, taking corresponding structure regions with the same angle point distribution difference degree as same structure regions of each structure, and then obtaining a search step length of the same structure regions of each structure to etch the circuit of the thermal printing sheet. The application can improve the efficiency of circuit etching of the thermal printing sheet.

This invention relates to the field of image processing technology, specifically to a visual quality inspection method for connectors in new energy vehicles. The method acquires an image of the connector pins; determines a local similarity coefficient based on the pixel value difference between each pixel and its neighboring pixels within each first cluster region obtained by dividing the pin image; determines a sharpness evaluation parameter for each first cluster region based on the difference in spatial coordinate gradient direction at each first pixel within each first cluster region; classifies each first cluster region as a tip region or a root region based on the sharpness evaluation parameter; determines a pixel value correction coefficient for each second pixel based on the pixel value distribution characteristics between second pixels within each second cluster region in the same root region; and corrects the pixel value of each second pixel based on the pixel value correction coefficient. Thus, the image is corrected using the pixel value correction coefficient, improving the detection accuracy when comparing the corrected image with a standard part image.

The invention relates to the technical field of image processing, in particular to a visual quality inspection method for a new energy automobile connector. The method comprises the steps of obtaining a pin image of a connector; determining a local similarity coefficient according to a pixel value difference between each pixel point and an adjacent pixel point in each first clustering region obtained by dividing the pin image; determining clear evaluation parameters of the first clustering areas according to the space coordinate gradient direction differences at the first pixel points in the first clustering areas; judging each first cluster region as a tip region or a root region according to the clear evaluation parameters; determining a pixel value correction coefficient of each second pixel point according to a pixel value distribution characteristic between the second pixel points in each second clustering region in the same root region; and correcting the pixel value of each second pixel point according to the pixel value correction coefficient, thereby performing correction processing on the image by using the pixel value correction coefficient, and improving the detection precision when the corrected image is compared with the standard component image.

The invention discloses an image compression method, an image decompression method and a system thereof, which are applied to the field of image processing. For each image area, the compression process comprises the following steps: calculating a pixel value difference value between each non-basic pixel point and a reference pixel point thereof; for the basic pixel points, the pixel values of the basic pixel points are stored according to the original data width and the original values; and for non-basic pixel points, the pixel values of the non-basic pixel points are compressed and stored according to the new data width and the pixel value difference value. Correspondingly, the decompression process comprises the following steps: for the basic pixel points, directly reading the pixel values of the basic pixel points from the compressed image; and for the non-basic pixel point, reading the pixel value difference value between the non-basic pixel point and the reference pixel point from the compressed image, converting the read pixel value difference value from the new data width to the original data width, and restoring the pixel value based on the converted pixel value difference value and the obtained pixel value of the reference pixel point. Therefore, the occupation of the transmission bandwidth and the storage space can be effectively reduced.

The application discloses a forest disturbance monitoring method, system, device and medium based on an image difference method, and relates to the field of forest monitoring.The method comprises the following steps: performing spectral index feature extraction on historical remote sensing images of a region to be monitored to obtain a remote sensing feature set; dividing the remote sensing feature set of the historical remote sensing images into two categories, i.e., disturbed forest and undisturbed forest, counting the reflectivity mean values of eight bands corresponding to the two types, selecting bands with larger differences in pixel value differences from a preset number of bands, and selecting three bands from the preset number of bands as set difference bands; obtaining a spectral feature map corresponding to a current period remote sensing image of the region to be monitored and a spectral feature map corresponding to a last period remote sensing image; and determining a current disturbed forest region of the region to be monitored by using an image difference method according to the current period spectral feature map and the last period spectral feature map and according to the preset difference bands.The application realizes large-range and fine real-time monitoring of forest disturbance.

Methods and apparatus are provided for reducing the dynamic range of an image. A first image and a second image have pixel values of a first bit depth. One or more peak regions and a representative pixel value for each peak region are identified in a histogram of pixel values in the first image. For pixel values in the first image that are within a peak region, a pixel value difference is computed as the difference between the pixel value of the peak region and the representative pixel value. For pixel values in the first image that are outside of a peak region, the pixel value difference is zero. Pixel values of the second image are transformed to reduce the bit depth to a second bit depth. The pixel value differences computed from the first image are then added to the pixel values of the transformed second image.

The invention discloses an underwear design parameter adjustment method and system based on image analysis, and relates to the technical field of image analysis, and the method comprises the following steps: constructing optical data of a reference object under a fitting site under a standard illumination condition; acquiring an underwear image of a fitting person under the fitting site, and acquiring a local reference image of the reference object at the same time; identifying a pixel value difference between the local reference image and the optical data; calculating a pixel gain and a pixel offset required by the underwear image based on the pixel value difference; correcting each pixel in the underwear image based on the pixel gain and the pixel offset; carrying out picture analysis processing on the corrected underwear image; and adjusting underwear design parameters based on the underwear image features. According to the method, image deviation caused by illumination condition changes can be effectively corrected, and the accuracy of image data is ensured, so that the accuracy and reliability of underwear design parameter adjustment are improved.

The application discloses an indoor three-dimensional reconstruction method and device based on a signed distance field, and when a signed distance field network and a neural radiance field network are trained, three-dimensional sparse point clouds corresponding to pixel points with large pixel value differences between rendered images and real images are introduced to introduce a detail correction loss, and meanwhile, an overall supervision loss constructed based on the rendered images and the real images is cooperated to optimize the signed distance field network and the neural radiance field network, so that the network prediction performance is stronger, the geometry shape and the illumination appearance of a high-quality reconstruction scene can be considered, and meanwhile, the loss of details such as furniture in an indoor scene can be prevented.

The application discloses a kind of underwear design parameter adjustment method and system based on image analysis, it is related to image analysis technical field, including the following steps: constructing optical data under standard illumination condition under reference object in fitting site;Acquire the underwear image of fitting person in the fitting site, and simultaneously acquire the local reference image of the reference object;Identify the pixel value difference between the local reference image and the optical data;Based on the pixel value difference, the pixel gain and pixel offset required by underwear image are calculated;Based on the pixel gain and pixel offset, each pixel in the underwear image is corrected;After the correction, the underwear image is processed by picture analysis;Based on the underwear image feature, adjust underwear design parameter.The application can effectively correct the image deviation caused by illumination condition change, ensure the accuracy of image data, so as to improve the accuracy and reliability of underwear design parameter adjustment.