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Color number self-adaptive decision making method and image compression method

A decision-making method and image compression technology, applied in image communication, digital video signal modification, television, etc., to achieve the effect of improving image compression efficiency

Active Publication Date: 2013-03-27
PEKING UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Obviously, for images with a small number of colors, there is still a lot of room for improvement in the compression performance of this method

Method used

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  • Color number self-adaptive decision making method and image compression method
  • Color number self-adaptive decision making method and image compression method
  • Color number self-adaptive decision making method and image compression method

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specific Embodiment approach

[0040] The invention utilizes color quantization distortion and distortion change rate to adaptively determine the number of color quantizations of different images, and uses color adaptive quantization results to perform PNG image compression, so as to realize improvement of image compression ratio under the condition of ensuring subjective quality without obvious distortion. A specific embodiment of the present invention is as follows:

[0041] 1. Adaptive decision-making method for the number of image colors in color quantization

[0042] Set the initial value N0 of color quantization, the initial value of iteration count i=0, the maximum number of colors MaxNum=256 and the increment Ns of the number of colors between two iterations, and the distortion change rate threshold T1 and distortion threshold T2 when color quantization ends;

[0043] The first step: adopt the color quantization algorithm based on the minimum variance to obtain the result when the image color quanti...

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Abstract

The invention provides a color number self-adaptive decision making method and an image compression method, and relates to the technical field of digital signal processing. The color number self-adaptive decision making method includes steps of researching given initial small color numbers; calculating corresponding image quantizing distortion and distortion change rate; and determining that the corresponding color number is the color number required for the final quantization if the image quantizing distortion and the distortion change rate is smaller than a threshold valve or the color number excesses the given maximum color number. The image compression method includes steps of acquiring reasonable color number of given images by the color number self-adaptive decision making method; then quantizing the images into given color number by a color self-adaptive quantizing algorithm; and compressing the images by means of PNG compression algorithm. The image compression method has the advantage of high compression efficiency and the like.

Description

technical field [0001] The invention relates to the technical field of digital signal processing, in particular to an adaptive decision-making method for the number of colors and an image compression method. Background technique [0002] PNG (Portable Network Graphics) image is one of the most popular image formats on the Internet at present. It is a lossless compression format that supports three color types of grayscale, true color and index image, and supports α channel at the same time. For grayscale images, it can support 1, 2, 4, 8 or 16-bit images; for color images, it can support 8 or 16-bit images. It can support color images with up to 256 colors when using indexed image compression. However, since the PNG image is a lossless compression algorithm, the compression ratio is not high, generally around 4:1 to 5:1. Take a 24-bit true-color image with a size of 256x256 as an example. If it is not compressed, each image needs about 192KB, and after PNG compression, it ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N7/26H04N19/147
Inventor 马思伟张新峰熊瑞勤高文
Owner PEKING UNIV
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