Lossless compression coding method for pure trichromatic picture data

Abstract

The invention relates to a lossless compression coding method for pure trichromatic picture data. The method comprises the following steps: comparing pixel value data of each pixel in a picture to becompressed with a specified pixel value, if the pixel value data of each pixel are equal to the specified pixel value, then recording as decimal 1, otherwise recording as decimal 0 and recording the value of the pixel; and sequentially comparing the decimal 1 with the decimal 0 for many times and combining the decimal 1 and the decimal 0 into one byte through an algorithm and recording the byte, circularly comparing until the pixel data are picture data file tails to be compressed, and finally generating a compressed new picture data file including the specified pixel value, all synthesized byte data and all stored pixel values. The invention provides a picture data lossless compression method for the lossless compression coding method for the pure trichromatic picture data, which can overcome the problems of low picture compression rate, insufficient compression effect and lossy compression in the prior art; and even scattered discontinuously repeated pixels can be recorded by using fewer bytes, so that the picture data compression rate is improved, and the picture data are kept complete and lossless.

Description

technical field [0001] The invention relates to the technical field of picture compression, in particular to a lossless compression encoding method for pure three-primary-color picture data. Background technique [0002] Currently, known image compression methods include lossy compression and lossless compression. [0003] The lossless compression method usually has run-length encoding. The basic principle is to represent adjacent pixels with the same color value in a scan line with two bytes. The first byte is a count value, which is used to specify the number of pixel repetitions. ; The second byte is the value of the specific pixel. The lossless compression method can better preserve the quality of the image, but if the pixels of the picture are variable, the pixel positions of the same value are also variable and scattered, which will result in the number of bytes used to record the count value of the number of repetitions of the specified pixel becomes larger, and two...

AI Technical Summary

Problems solved by technology

[0007] Fractal compression (en: Fractal compression); looking for self-similar parts within a graph leads to excessive compression time

[0008] Compression and decompression using lossy compression methods are relatively slow, and the decompressed pictures are incomplete, which limits the use of some occasions that require complete pictures

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