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112 results about "Color quantization" patented technology

In computer graphics, color quantization or color image quantization is quantization applied to color spaces; it is a process that reduces the number of distinct colors used in an image, usually with the intention that the new image should be as visually similar as possible to the original image. Computer algorithms to perform color quantization on bitmaps have been studied since the 1970s. Color quantization is critical for displaying images with many colors on devices that can only display a limited number of colors, usually due to memory limitations, and enables efficient compression of certain types of images.

Fixed-rate block-based image compression with inferred pixel values

An image processing system includes an image encoder system and a image decoder system that are coupled together. The image encoder system includes a block decomposer and a block encoder that are coupled together. The block encoder includes a color quantizer and a bitmap construction module. The block decomposer breaks an original image into blocks. Each block is then processed by the block encoder. Specifically, the color quantizer selects some number of base points, or codewords, that serve as reference pixel values, such as colors, from which quantized pixel values are derived. The bitmap construction module then maps each pixel colors to one of the derived quantized colors. The codewords and bitmap are output as encoded image blocks. The decoder system includes a block decoder. The block decoder includes a block type detector, one or more decoder units, and an output selector. Using the codewords of the encoded data blocks, the comparator and the decoder units determine the quantized colors for the encoded image block and map each pixel to one of the quantized colors. The output selector outputs the appropriate color, which is ordered in an image composer with the other decoded blocks to output an image representative of the original image. A method for encoding an original image and for decoding the encoded image to generate a representation of the original image is also disclosed.
Owner:S3 GRAPHICS

Video key frame extraction method based on color quantization and clusters

InactiveCN103065153ALow type dependencyAvoid redundant selectionCharacter and pattern recognitionTelevision systemsCanonical quantizationFrame difference
The invention discloses a video key frame extraction method based on color quantization and clusters. The method comprises the steps of loading video data flow; conducting single frame scanning on video flow; conducting the color quantization on obtained frame images, and extracting main color features of the frame images going through quantization; calculating similarity of adjacent frames so as to obtain adjacent frame difference; conducting shot boundary detection according to the adjacent frame difference; conducting shot classification on intersected shots and extracting a representative frame of each shot; and conducting compression clustering on the sequence of the representative frames so as to obtain a key frame sequence. According to the method, the color quantization is conducted on the single frame images so that main color of the images is extracted, frame difference calculation is conducted through the cluster feature similarity calculation method based on color features of the clusters so that the shot boundary detection is realized, and finally clustering according to the compression ratio is conducted on the extracted representative frames. Due to the fact that he whole process is low in dependency on video formats and types, the method has good universality and adaptability, is simple in calculation and low in space consumption, and can effectively avoid the phenomenon of key frame selection redundancy, control the number and quality of the key frames, and realize control of the video compression ratio.
Owner:SOUTHWEAT UNIV OF SCI & TECH

Vector-quantization-based overall and local color image searching method

The invention relates to a vector-quantization-based overall and local color image searching method. The invention provides a new color image searching method, and relates to the field of an image processing technology. The method comprises the steps of converting an RGB (red, green and Blue) color space into an HSV (Hue, Saturation, Value) color space, performing relatively accurate clustering division on the color space by applying a neural-network-based competitive learning algorithm training code book; describing a space distribution situation of colors by introducing a color transfer matrix; combining the two characteristics, namely an index column diagram and a main color transfer matrix, so as to perform the similarity measurement; processing images by applying a morphological opening-and-closing operation, highlighting a target contour so as to extract a local interest area so as to highlight an important area and limit background information. The color image searching method overcomes the defects that the color space distribution description is not enough and the background information cannot be effectively limited by using the overall color histogram method. By using the vector-quantization-based overall and local color image searching method, the color quantization is relatively accurate, the matching effect is relatively good, and the vector-quantization-based overall and local color image searching method is an effective method for further improving the researching efficiency.
Owner:CHONGQING UNIV OF POSTS & TELECOMM

High-resolution remote sensing image segmentation method based on inter-scale mapping

The invention discloses a high-resolution remote sensing image segmentation method based on inter-scale mapping. The high-resolution remote sensing image segmentation method has the advantages that aiming at geographical object extraction involved in objet-level change detection, the high-resolution remote sensing image multi-scale segmentation method based on wavelet transform and an improved JSEG (joint systems engineering group) algorithm is provided; aiming at a key problem that a conventional JSEG algorithm affects segmentation accuracy in high-resolution remote sensing image segmentation, a corresponding improvement strategy is adopted to achieve a good effect; wavelet transform is introduced to serve as a multi-scale analysis tool, excessive rough color quantization of the conventional JSEG algorithm is abandoned, and thus, detail information in original images is kept to the utmost; a novel inter-scale segmentation result mapping mechanism is set up, image segmentation of a current scale is realized on the basis of a segmentation result of a previous scale, and correction of the segmentation result of the previous scale is also realized, and thus, accumulation of inter-scale segmentation errors is decreased effectively; finally, an improved multi-scale segmentation strategy and an improved region merging strategy are provided, and over-segmentation and mistaken merging are effectively reduced.
Owner:HOHAI UNIV

Method and device for making image cartoony and fusing image with 2D code

ActiveCN106599965AAvoid the problem of dark and blurry picture qualityImprove continuityImage enhancementImage analysisColor quantizationContour line
The invention discloses a method and device for making an image cartoony and fusing the image with a 2D code, and relates to the technical fields of image processing and 2D codes. The method comprises that an input image is made cartoony; a standard 2D code is generated according to an input text; and the cartoony image is fused with the standard 2D code to form a cartoon 2D code. When the image is made cartoony, a Gaussian difference operator is used to describe a contour line along the tangential flow field in the edge, and double-side Gaussian smoothing and color quantification are carried out. When the image is fused with the 2D code, fusion is carried out on the basis of a module, and under the condition that content included by the 2D code is not changed, the visual display effect of the 2D code approaches a binary result of the cartoony image as possible; and fusion is carried out on the basis of image pixels. The device comprises an image cartoonlization module, a standard 2D code generation module and a cartoony 2D code fusion module. According to the invention, image cartoonlization effectively remove concrete content of the image, so that the 2D code is fused with the image in a better way, and the fused 2D code is more beautiful.
Owner:北京矩石科技有限公司

Outdoor traffic sign identification method under low-illumination scene

The invention discloses an outdoor traffic sign identification method under a low-illumination scene. The method comprises the following steps: allowing a low-illumination scene image containing traffic signs to be subjected to HSV conversion, calculating an integration histogram of the low-illumination scene image and detecting a traffic sign interest area through a threshold value method and a mathematical morphology method; adopting an SIFT algorithm to calculate descriptors of scale-changeless characteristic points of the traffic sign interest area and matching the descriptors with an image in a standard library so as to obtain matched point pairs; taking the coordinates of the scale-changeless characteristic points as image center spots to obtain subimages; respectively calculating the color-improved quantification histograms, which are fused with color tone, saturation and brightness, of the subimages, as well as the normalized color-improved histograms; calculating an included angle of two histograms of two matched points of the matched point pairs; removing the matched point pairs with big-different included angle; removing the matched point without a matching point; and obtaining the identification result of the traffic signs of the low-illumination scene image according to the number of the matched points. The method provided by the invention has the advantages of stronger robustness, and higher accuracy rate.
Owner:GUANGDONG UNIV OF TECH

Refined embroidery texture migration method based on sample domain

The invention discloses a refined embroidery texture migration method based on a sample domain, which comprises the following steps: in a model training stage, based on a cyclic generative adversarialnetwork, adding a Waserstein loss item, a feature matching loss item and an MS-in loss item into a loss function, and performing feature matching on the loss item and the MS-in loss item; according to the SSIM loss item, a self-attention mechanism is added to a generator G network, and a resolution enhancement method from coarse to fine is introduced. A training model is used for synthesizing embroidery textures; performing color quantization processing based on self-organizing network mapping on the input embroidery vector design drawing, performing color correction on the generated embroidery textures through the quantization method, and finally combining the embroidery textures with the generated normal map to obtain an embroidery texture map which meets the three-dimensional display requirement and has both embroidery colors and concave-convex textures. According to the method, rapid generation from image design to refined embroidery texture is realized, and the rework rate of production personnel is reduced while the communication efficiency of the design personnel is improved.
Owner:SHANGHAI LINCTEX DIGITAL TECH CO LTD

Color quantification method based on density peak value

InactiveCN104899899AImprove performanceColor quantization is efficient and robustImage analysisDistance matrixDensity based
The invention discloses a color quantification method based on a density peak value, and the method comprises the steps: letting an image comprise N pixel points, calculating the Euclidean distances dij between each two pixel points, and building a distance matrix D; letting a cut-off distance be dc, and calculating a local density rho (i) of each pixel point according to the distance matrix D; for each pixel point, finding all pixel points which have higher local densities than the pixel point; finding the Euclidean distances from the pixel point to the pixel points with higher local densities according to the distance matrix D, and defining a minimum Euclidean distance delta (i); calculating a parameter gamma (i), equal to rho (i) * delta (i), of each pixel point, enabling all parameters gamma (i) to be arranged in a descending order, and selecting the pixel points corresponding to the front K parameters gamma (i) as cluster center points; enabling each pixel point after the K pixel points to be ranked in types corresponding to the cluster center points, and then employing a mean value of each type to represent the pixel value of this type, thereby completing the color quantification. The method is good in performance, can effectively and robustly achieve color quantification, and can flexibly meet different needs.
Owner:TIANJIN UNIV
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