Multispectral image compression using eigen-region-based segmentation

In the study, we present an effective segmentation technique for multispectral image compression. This technique fully exploits the spectral and spatial correlation in the data. The original image is first divided into some proper eigen-regions according to the local terrain characteristics of the image. Then, each region image is transformed by the corresponding KL transformation function and results in an eigen-region image for further compression. Simulation tests performed on Landsat TM images have demonstrated that the proposed compression scheme is suitable for multispectral image.