Coding of spectrally homogeneous regions in multispectral image compression

In this paper we present a new approach in the compression of multispectral images. It is based on the merging of two processing tools, namely Karhunen-Loeve transform (KLT) as a spectral decorrelator, and object based image coding schemes. The potential use of the principal components analysis in multispectral imagery is described and it is used to perform a multispectral segmentation. This segmentation is taken as the basis for a specific spectral decorrelation for each segmented class. The resulting eigen images present lower variance than those obtained with classical KLT approaches. Each of the eigen regions is coded spatially using a shape adaptive DCT algorithm. The method outperforms non-region multispectral KLT+DCT schemes as well as JPEG, while adding region based functionalities.