The compression of a sequence of satellite images based on change detection
A 'loss-effective' compression method which based on the change detection of raw image data is proposed for dealing with a sequence of satellite images. The average compression ratio we gained, compared with some typical satellite image formats, is about 2:1 to 3 :1. This sounds not so impressive when compared with the most current compression techniques which used in multimedia processing. However, some information will be lost in those methods, while our approach is information-loss effective, which is crucial for further satellite image analysis. Moreover, the framework can be combined with different compression algorithms to obtain different trade-offs between the compression ratio and the computation time. Experimental results based on real satellite images are included. Finally, other issues including the further optimization of the methods and some other possible applications of the method are discussed.