Research On Fractal Image Compression Based On The Cluster

The 21st century is an age of information, people working in the life of a large number of contacts with images, and spread among each other, in order to facilitate faster transmission of images, image compression technology research has become very urgent. In 1987 by the American mathematician Barnsley and Sloan [1] proposed fractal image compression coding technology, since then Jacquin [2] first realize the full automatic fractal coding and bring about a breakthrough in the field of fractal image compression. Fractal image compression technology based on this algorithm and become a new field.The image compression coding which based on fractal is a new coding method. It uses the self-similarity and the proportion properties of image; through reduce the geometry of the image to achieve compression of image data. In the fractal coding, an image is denoted by a similar compressed affine transformation and the reconstruction of image compression is the fixed point of conversion, the parameter of compression affine transformation buildup the fractal code of original image. Fractal decoding is a simple process of fast iterative. The decoding image is denoted by the sub-compact code that transform in the role of any approximation to the initial image.In recent years, fractal image coding has aroused great interest in the field of image compression. As we all know, a long-time cost is the main shortcoming of this coding technology, it has become the most important obstacle for its high-performance and practicality. So the fractal speed up coding methods has become a hot research point in recent years. This article will try to use the particle swarm optimization (QPSO) [3] which based on the quantum act, the fuzzy clustering algorithm optimization, the genetic algorithms and the quad tree partition method in a combination in fractal image compression. The results show that the application of these types algorithms improved fractal image compression rate greatly.The full article is divided into six chapters. At the first the paper mainly introduces the image compression technology, and the image compression research result within the past 10 years; the foundation and development of the fractal geometry, the geometric features, the nature and measurement of fractal, the theory of fractal image compression, including mapping, collage theorem, iterative function system and fractal image compression codec process;. In the text , it analysis the feature of the fractal image compression , introduces the particle group arithmetic, optimized particle group arithmetic which based on quantum behavior and fuzzy clustering algorithm, the advantages and disadvantages of the algorithms were compared, introduces the fractal image compression method that self-adaptive block and the four-fork-split comminute method, combined the genetic algorithms and quad tree partition method in fractal image compression . All the algorithm will be applied in fractal image compression, the results show that the algorithm applied to the fractal image compression increase the compression rate, it shows that the algorithm has a practical significance. At last the authour gives the summary and outlook, pointing out the direction for future research work and vision.