Research On The Image Compression Coding Based On Generalized Finite Automata

With the rapid development of multimedia technology in recent years, the digital image transmission plays a very important role in communication field. Digital images generally include a great deal of information, so the compression technology becomes the key of the research. On this occasion, it inevitably becomes one of the most important directions in the field of communication and signal processing to seek after the effective image coding algorithm. The technique of Finite Automata has a potential capability of improving coding performance. However, the development of the image coding based on FA has not been perfect. So in the paper, an in-depth study of static image Generalized Finite Automata (GFA) coding algorithm is conducted. The major jobs are described as follows:(1) Basic knowledge of image and main methods of image compression are introduced. At first, the development of image compression coding is reviewed simply; then the estimation methods of image quality are discussed, providing an academic preparation for image compression coding.(2) Depending on the analysis of principle that wavelet-base selected by static image compression coding, the most suitable wavelet for GFA coding is selected after comparing groups of the wavelet-base to execute the pretreatment.(3) The background and the development of the finite automata are reviewed. Besides, the basic conceptions and symbols of the finite automata are introduced in details. The most important aspects of this section are the detecting of images'self-similarity and the finite automata for multiresolution image.(4) According to the principle of self-similarity, the GFA compression algorithm is designed. Then this method is applied to the gray images, and the effectiveness of the method is proved.Finally, the research work involved in the thesis is summarized and the future developments in GFA method are forecast.