RGB565 true color image lossy compression and decompression method

Abstract

The invention discloses an RGB565 true color image lossy compression and decompression method. Firstly, original RGB image data are separated into monochromatic R ordered data, monochromatic G ordered data and monochromatic B ordered data and are arranged into an 8*8 matrix, then discrete cosine transformation is performed on the data, rounding is directly performed on direct-current components generated after transformation, data quantization is performed on alternating-current components, Z-shaped scanning is performed on quantized matrix data blocks, and zero values in the data are integrated; secondly, compression coding is performed on the quantized data, and Z-shaped inverse scanning is performed after decoding is performed; finally, inverse discrete cosine transformation is performed on the data, the data components are combined, and decompressed RGB image data are obtained. Under the premise that it is guaranteed that images are undistorted, the method increases the compression ratio of the image data, and can obtain clear real characters in a decompressed mode, reduce transmission amount of the data, and save transmission time of the data.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a method for lossy compression and decompression of RGB565 true color images. Background technique [0002] With the development of modern applications and computer technology, digital images will be used in more and more application fields. At present, the requirements for image processing in embedded products have become higher and higher. Whether the image information can be effectively stored and displayed An important point of product design. However, due to the large amount of digital image data, it is currently facing problems such as transmission and storage of digital image information, so it is very necessary to use image compression technology to reduce the image data stored and transmitted. [0003] The theoretical basis of image compression is Shannon's information theory and coding theory. The basic idea is to get rid of the redundancy in the i...

AI Technical Summary

Problems solved by technology

However, most embedded products currently use RGB565 format true color image data. Although adjacent pixels have similar colors, it is rare to find a large number of adjacent pixels with exactly the same color. There are few consecutive pixels, and there are fewer consecutive pixels with the same color value in multiple rows

Traditional RLE uses basic repetitive data statistics and does not compress irrelevant high-frequency information, so direct application of traditional RLE cannot guarantee an ideal compression effect and high-quality images

[0005] At present, there are also some researches on color image compression, but all of them are deficient. They cannot be compressed with a high compression rate, and cannot provide clear realistic text, which needs to be further improved.

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