Adaptive data compression for efficient sequential transmission and change updating of remote sensing images

In this paper, a selective data compression scheme is developed to combine the need for efficient data transmission and the receivers´ interest in changes presented in the data by taking the advantage of the fact that receivers hold a copy of previous data. Three-step pre-processing is introduced in this paper. Firstly we separate the unchanged areas (the majority) of the image from the changed areas between successive images of the same area. Secondly, the bands which are sensitive to the changes are identified with the aid of statistical measures. Finally, a binary index image of each band is generated to indicate the two categories. Following this pre-processing, compression of the unchanged areas and changed areas is conducted separately. In this way, different compression algorithms can be applied to each case. As the majority data will be unchanged and only a subset of bands reflects the changes, high compression rate is achievable.