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.