Research On Algorithms For Fractal Image Encoding

Image is one of the most important carriers for communication in our life, and it's the utmost medium containing information. As all we known, the data quantity of digital image is so large that it should be compressed for high-speed transmission and store. So image encoding has become one of the key technologies on which the digital society depends.In existed methods for image compression, fractal image compression, as a new scheme of image compression, has received a great deal of attention and study from researchers all over the world in the field of image compression because of its desirable properties such as fast decoding, resolution independence of decoded image and high compression ratio. However, there's an especially unsatisfying problem in this method: too long encoding time. Mainly because of the considerable number of domain blocks to compare with for each range block in encoding phase, which, in fact, prevent fractal image compression from becoming a practical method for image compression, hence fast encoding has become a hot issue in fractal image compression. Existed fast encoding methods are often at the cost of image quality, or can only obtain poor speed-up ratio.In this paper, a fast method based on comparing with a preset block is proposed on the basis of the algorithm based on shape feature. It is much faster than the basic fractal algorithm and better than the algorithm based on shape feature. However, there are still some shortcomings in the proposed method. So an improved method based on mean deviation-ordered is proposed aim at the two shortcomings of the method based on comparing with a preset block, and it's better at complexity and performance.