Research On Image Compression Based On Fractal Method

Image is the important carrier in our life and contains the most information. Because digital image contains a great deal of data, it must be compressed effectively in order to be transferred with high speed and stored. So image compression technique has important real-life meaning for information technology.Recently, there are hundreds of image compression methods, but the effect of compression, compression ratio and the time of coding and encoding can not satisfied with the needs of information era. So image compression needs more development. Because the traditional coding methods have generally been formulary, numbers of new methods come forth in recent years with the development of many new theories. Fractal image coding is one of the new coding methods. Because fractal image coding possesses the novel ideas and high compress ratio, it has attracted many researchers. Fractal image coding is a compression method with good development and has enormous development potentiality.Fractal image coding is a coding method that sprang up newly in the 1990s last century. It based on an image of self-similarity and thinks over the relationships between some and during the part, as well as the relationships between some and the whole. There are abundant of self-similarity geometry in the world, so fractal image coding is in a very large range to suit.Fractal image coding is based on Collage Theorem. For a given image, it searches a series of contractive map which compose Iterative Function System and approximate the given image. Because we only note the parameter, fractal image coding has high compression ratio. Fractal image coding has high PSNR and good vision under high compression ratio and other methods cannot attain.Fractal image encoding is based on Iterative Function System and rebuilds the image by sometimes iterative. Because the resolution ratio of encoded image has nothing to do with the size of original image, the size of the encoded image can be shrunk or enlarged as much as possible, furthermore this can not destroy the elaborate structure of the encoded image. Fractal image coding and encoding has developed for over 10 years, however its potentiality has not been excavated out, for example:its compression ratio isn't so high, the coding time is not so short and it is not the very idea to the compression effect, so recently in the image coding methods, fractal image coding can not occupy the leading position. There are a lot of places in the fractal image coding less than satisfaction, the slow coding speed is one of the factors that prevent it from being practicability. This paper analyses the factors that affect the speed of fractal image coding, and an Improved Algorithm of Fractal Coding based on sorting the contracted domain pool is presented. Two parameters are used to sort domain pool:the number of hopping and the variance of continuing positive and negative pixels in the given block. With the help of the parameters, the number of domain blocks examined by a range block is reduced dramatically, and thus, the sort of domain blocks results in a considerable acceleration of the encoding process.To compare with the method done by C.K.Lee that sorts the contracted domain pool in terms of their local variances, the proposed method is proved to be a better way to improve the quality of pictures with a little more time in encoding.