Research On The Image Compression Coding Based On Wavelet Transform

With the development of modern communication technology, computer network technology and information processing technology, image information processing, storage and transmission play more and more important role in social life. The compression coding solution for image storage and transmission gradually become the research hotspot around the globe. The traditional image coding method is better to remove statistical redundancy of image information, but it has obvious block effection in high compression rate. The wavelet transform have excellent time-frequency domain and multi-resolution analysis that overcome the traditional shortcomings of image compression algorithms. As a result, image compression based on wavelet analysis algorithm has held a dominant position.This paper introduces the existing compression coding technology and wavelet transform coding theory. And then make simulation of image by the wavelet transform and analysis the characteristics of each sub-band.Reveals the wavelet transform image compression in real terms -- with a small amount of the most important wavelet coefficients to reconstruct the whole image and achieve the purpose of image compression.By analyzing two classic encoding algorithms of the wavelet transform: Embedded Zerotree Coding and Set Partitioning in Hierarchical Trees. According to the simulation result, EZW is easy to realize but has low coding efficiency; SPITH improves the coding efficiency, but the algorithm complexity is not conducive for hardware implementation. This paper designs solution for EZW algorithm's shortcomings. The main improvement has been made in four areas:â‘ improvement from the traditional wavelet transform to integer wavelet transform.â‘¡low-frequency sub-band coding using DPCM.â‘¢The main scan method improvement.â‘£Increased vice scanning accuracy. The improved algorithm is a better algorithm for improving the PSNR of compressed images and restoring image quality.