Near-Lossless Compression of Multispectral Remote Sensing Image Based on Classified K-L Transform
基于分类K—L变换的多波段遥感图像近无损压缩方法

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.