The Digital Image Compression Based On Embedded Zerotree Wavelet Algorithm Research

A rich and colorful of digital images is an important source of information for people to understand the world. Information storage and transmission of higher efficiency is needed in order to solve the contradiction of unlimited information and limited broadband, especially in the huge field of digital image communication. Because the large amount of information of the image, so it has high requirements to storage devices and line broadband. If there is no more effective digital image coding techniques, which will restrict the development of digital image communication. We study the purpose of digital image compression is a common feature of certain types of digital images to identify efficient coding techniques for digital image encoding and decoding, in order to reduce the image storage and transmission burden on the network or server for fast digital image transmission and real-time processing.This paper I detailed study and experimental digital image wavelet compression algorithm. First, the paper describes digital image compression research status, the compression algorithm based on wavelet transform theory and its application. Second, focusing on the embedded zero-tree wavelet and multi-level collection of the split tree algorithm conducted a detailed study on the EZW and SPIHT algorithm uses the zero-tree structure to compress the basis of the data, and illustrates the advantages and disadvantages of the EZW algorithm and the SPIHT algorithm. Finally, the proposed improved algorithm based on EZW and SPIHT algorithm based on. Improved algorithm includes the following aspects:(1) This paper analyzes the advantages and disadvantages of the EZW algorithm, and made a wavelet transform to enhance the transformation format, as well as the combination of the zero-tree coding and entropy coding. This article alone high-frequency sub-band coding processing and low-frequency sub-band, and make Matlab simulation experiments.(2) Brothers assumption for the original SPIHT algorithm, the re-definition of the zero-tree structure, and will be based on the idea of the state bitmap added to the algorithm, re-write the modified algorithm, and make Matlab simulation experiments.Improved algorithm is simulated the compression experiment with lena.bmp(256*256). The experiment has achieved satisfactory results. The experimental results compared with the classic the EZW. SPIHT operator to verify the feasibility and correctness of the improved algorithm.