Compression Based On Wavelet Transform Image Coding

Digital image compression has always been the hot spot in the field of information processing technology especially in the information society where 'digital' has become more and more popular. Computer networks and digital products bring people the colorful vision menu. At the same time they make it necessary to compress and coding the vast amount of vision information, in order to store and send them more conveniently.The Method based on the DCT transformation has been the center technology for most of the digital image and video coding standards, since it features on good de-correlation and energy compression. However, deep researches and wide application find that DCT transforming doesn't have the characters of good time-frequency location and the whole transformation, thus block-effect and ring-effect will inevitably emerge in the compressed pictures based on the DCT transforming especially when the compression rate gets larger, block-effect will become the major factor to restrict the quality of DCT transformation coding. Small wave transformation is a time-frequency information analysis method. It has the characteristics of multi-analysis. It also has the ability to indicate signal local qualities in either time or frequency, which can process the imbalanced signals with effective signal indication and to make them gain fast application in the stereo image and video frequency . Furthermore, because of wavelet transformation's unique ability of multi-resolution and direction selection (like that of human eyes), it has replaced DCT transformation in JPEG2000 to become the image de-correlation transformation standards.This paper studies the digital image coding based on wavelet transformation.Firstly, it tells you some information about digital image compression coding, including image compression fundamentals, types of digital image and the commonly used methods of compression coding, meanwhile, it makes a brief introduction and comparison of JPEG and JPEG2000 for both state image compression standards. Secondly, it makes an introduction and analysis of correlated theories about wavelet transformation. Then it discusses the applications of wavelet transformation in the static digital image coding. It gives the explanation and analysis about embedded wavelet to EZW and SPHIT coding methods and its application of static images compression. It gives an improved SPIHT coding algorithm based on lifting-wavelet...