Research Of Wavelet Transform Image Compression Based On Potential Fuzzy Clustering

Image compression becomes the hotspot of international academia along with the wide use of network and the rapid development of the multimedia techniques. Wavelet analysis is a novel field with rapid development in modern mathematics; not only it has far-reaching meanings of theory ,but also has very prospect of application . Image compression based on Wavelet Transform is one of the important applications for wavelet analysis. It has advantages of high compression rate and high compression speed, at the same time it also has the shortcoming of edge fuzzy phenomenon under low bit rates. In this paper, our purpose is to think of how to save more information of the edge and texture of the original image, to reduce the edge fuzzy phenomenon and to improve the subjective quantity of the reconstructed image under low bit rates.Firstly, image compression algorithms based on wavelet transform are summarized and we analyze the current state ,exiting problem and several directions of development of these techniques. And then, in order to reduce the edge fuzzy phenomenon, which occurs in the wavelet-based image compression algorithms under low bit rates, a new method of wavelet image compression based on potential fuzzy clustering has been presented in this paper. The potential fuzzy clustering method is applied to quantize the high frequency detail sub band images' wavelet coefficients after the image has been decomposed. This method considers the statistical characteristics of each high frequency sub band images' wavelet coefficients and the importance of high frequency sub band images' wavelet coefficients for saving the edge and texture information of the original image. At the same time it makes the best of the characteristics of fuzzy set. The experimental results show that this method can keep more information of the edge and texture of the original image under low bit rates, the edge fuzzy phenomenon is reduced to some extent, and the subjective quality of the reconstructed image is improved to some extent.