%0 Journal Article
%T Near-Lossless Compression of Multispectral Remote Sensing Image Based on Classified K-L Transform<br>基于分类K—L变换的多波段遥感图像近无损压缩方法
%A NI Lin
%A <br>倪林
%J 遥感学报
%D 2001
%I 
%X The spatial and spectral decorrelation are important steps in the compression of multispectral remote sensing image. To obtain better decorrelation effect, in this paper, the vector quantization is employed into the compression of multispectral remote sensing image in order to decorrelate the spectral vectors corresponding to the same objects. Then the classified K_L transform is used to reduce the spectral correlation of quantization error image. Finally, the prediction tree is adopted to reduce the spectral correlation of structure and the spatial correlation of the eigenimages. The experimemtal results show that satisfactory compression effect, has been achieved using the methods introduced in this paper.
%K vector quantization
%K classified K_L transform
%K prediction tree<br>矢量量化
%K 分类K－L变换
%K 预测树
%K 遥感图像
%K 近无损压缩
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=E62459D214FD64A3C8082E4ED1ABABED5711027BBBDDD35B&cid=A41A70F4AB56AB1B&jid=F926358B31AC94511E4382C083F7683C&aid=E0ACA412856A1F0E&yid=14E7EF987E4155E6&vid=94C357A881DFC066&iid=38B194292C032A66&sid=EF27C460877D3C9F&eid=527AEE9F3446633A&journal_id=1007-4619&journal_name=遥感学报&referenced_num=4&reference_num=10