%0 Journal Article
%T An Improved Zero-tree Wavelet Image Compression Algorithm<br>一种改进的零树小波图像压缩算法
%A XIA Yong
%A TIAN Jie
%A DAI Ru-wei
%A <br>夏勇
%A 田捷
%A 戴汝为
%J 软件学报
%D 1999
%I 
%X Gibbs phenomenon, which occurs in the wavelet-based image compression algorithms under low bit rates, remains an open question for many years. The main cause is that purely-pixel-value-based MSE(mean square error) criteria can not allocate enough bits to the wavelet coefficients corresponding to edges in image. With detail analysis of zero-tree wavelet image compression algorithm originally proposed by Shapiro and then well-modified by Said and Pearlman, the algorithm is improved by suppressing high frequency noises as well as adaptively quantizing coefficients around edges. Experimental results are comparatively given. The main contribution of this paper is the idea of combination of recognition and compression. With the aid of the spatial localization property of wavelet transform, a very flexible bit allocation scheme can be realized, and therefore Gibbs phenomenon is reduced to some extent.
%K Image compression
%K wavelet transform
%K zero-tree algorithm
%K human visual characteristics
%K adaptive quantization
%K recognition and compression<br>图像压缩
%K 小波变换
%K 零树算法
%K 人体视觉特性
%K 自适应量化
%K 识别与压缩.
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=09E7B271153A14263221646F36EE285E&yid=B914830F5B1D1078&vid=F3090AE9B60B7ED1&iid=B31275AF3241DB2D&sid=C824C8F9F54AE9B9&eid=039DCCB9394D9766&journal_id=1000-9825&journal_name=软件学报&referenced_num=5&reference_num=15