Fractal Image Compression Based On The Theory Of Wavelet

Under the trend of information and digitization, Image memory and transmission set the very high request for the technology of digital image compression, therefore,how to compress the image with high effection and no distortion or a lot distortion is an emphasis in research to people.Because the wavelet can solve diamond effect effetely and resolve mosquito_noise basically ,it is an important way of research in the field of image compression nowadays.But what is defect is no making use of the similarity among Subbands of the Wavelet domain.Thus make the compressiong rate of coding image not highly.Its Complexity is high to use Jacquin fractal encoding method,and its similarity is not well to more images and its compression rate is not high,but its decoding is very fast.So we can use advantages from shortcomings,and make full use of the similarities of subbands after wavelet translation,and use fractal compression methods based on wavelets .Therefore we prove a new way for the fields of image compression.These thesis put forward a new method of fractal image encodings of compression based on wavelets under the research of distribution of coefficients after wavelets translation. At first we use Mallat_wavelet translation to primary image,then divide translated coefficients into corresponding Ranges ang Domains according to Jacquin fractal encoding method,and draw into partial Haar translation on the basis of characteristics which energy concentrate in low parts after wavelets translation,and make the matching calculation replacing low_ frequency for primary image between Rangs and Domains fast in the course of search,then we can improve the rate of encoding.