Research On Fast Fractal Image Compress Coding

As the science and technology quickly develops, The Information Revolution which was taken with by computer technology has made humanity going into society of information. The multimedia technology based on image enriches our lives. However if there is no highly effective compression approach, image communication can not be achieved. Therefore, Image compression is the key and bottleneck of multimedia technology.Up to now, some mature technologies have been developed in the area of image compression, such as DCT (Discrete Cosine Transform) and Huffman Code. Moreover, a series of international standards based on these coding algorithms, for example, BIG, JPEG, JPEG-2000, H.261, H.263, MPEG-1, MPEG-2, MPEG-4 and MPEG-7.Recently, many new coding methods have been proposed, such as Sub Band Coding, Wavelet Transform Coding and Fractal Image Coding. Especially, FIC has attracted the attention of many native or abroad researchers since it was introduced into the field of image coding, due to its advantages, such as high compression performance, simple and fast decoding process, novel encoding and decoding theory and resolution independence.But, image coding based on fractal theory has its own inherent defects: expensive computational cost in the encoding process and image recovery at high ratio of compression is not good enough. Therefore, this paper studies mainly how to reduce runtime in the encoding process while maintaining the reconstructed image quality. The main study of article is:(1) A fast method for fractal image coding based on K-mean clustering is proposed. During the process of coding, we classify the range blocks and the domain blocks in use of the better class performance and self-adjustability of K-mean clustering. In this way, coding time is reduced greatly. Compare with current methods, this method has desirable properties such as no parameter which need to be set before, better self-adjustability and accurate classify.(2) A fast method for fractal image coding based on based on correlation coefficient and variance is proposed. This method mainly optimizes the search process by using two gate values.(3) Unify the two methods proposed before, form a new coding scheme.(4) Tile effect is common defect at high compression rate all block-based image compression methods. There is no exception for fractal image coding. So we proposed a simple but effective method to reduce the tile effect in use of resolution independence. Firstly, we decode the image at lower resolution. And then, we employ the bilinear interpolation technique to reconstruct the image at the same resolution.(5) Construct models for all coding schemes and implement all algorithms proposed using C++ language in computer. Compare the experiment results, validate the improved effect.Experimental results indicate that the proposed methods in this paper improve the coding speed while maintaining the reconstructed image quality and the performance is better than other methods.