Graphic image compression method

Abstract

The invention proposes a graphic image compression method, which is mainly for lossy compression of graphic images. In a traditional method, after an image is subjected to wavelet transform, an encoding method is adopted to directly encode a wavelet coefficient matrix; the compression rate of the compression method often cannot satisfy multiple images nowadays and the relationship between various pixels of the image is ignored. The method of the invention is used for modeling the relationship between an image distortion function and a bit rate function for the wavelet coefficient matrix after the wavelet transform, and the relationship between an optimal compression ratio and various pixels of the image is fully considered. The method comprises the following steps: firstly, performing three times of wavelet transform on an original image, and obtaining the wavelet coefficient matrix about the image; secondly, establishing a compression function, that is a distortion function, establishing a mathematical model of the distortion function and the bit rate function of the image in each image subblock, and then reversely substituting into the mathematical model for solving to obtain the optimized wavelet coefficient matrix under the current background; and finally, using an SPIHT encoding method to encode the optimized wavelet coefficient.

Description

technical field [0001] The invention relates to the field of computer information technology, in particular to the field of compression and transmission of graphic images. [0002] technical background [0003] With the increasing normalization of digital life and the acceleration of updating of various hardware devices, the collected data, whether it is image data or graphics, is growing at a geometric rate. These rapidly growing data have brought a huge burden to storage, processing and transmission. As an important part of image processing, image compression has always been concerned by researchers. Image compression algorithm from the initial research on coding methods to the later research on space transformation coding, with the establishment of wavelet theory, fractal theory, artificial neural network theory and visual simulation theory, image compression coding methods are moving towards higher compression ratio and Better compression is in the works. [0004] Imag...

AI Technical Summary

Problems solved by technology

[0005] Traditional lossy compression methods can be divided into predictive coding, change-based methods, fractal-based methods, visual characteristics-based and vector quantization compression according to principles. Image details cannot be accurately described, and the higher the compression ratio, the greater the image reconstruction error, and it is difficult to directly describe the required image accuracy and compression ratio

Images