Improving JPEG performance in conjunction with cloud editing for remote sensing applications

In this paper, we propose an improved version of JPEG coding for compressin g remote sensing images obtained by optical sensors onboard microsatellites , The approach involves expanding cloud features to include their cloud-lan d transitions, thereby simplifying their coding and subsequent compression. The system is fully automatic and appropriate for onboard implementation. Its improvement in coding stems from the realization that a large number of bits are used for coding the blocks that contain the transition regions be tween bright clouds, if present in the image, and the dark background. A fu lly automatic cloud-segmentation algorithm is therefore used to identify th e external boundaries of the clouds, then smooth the corresponding blocks p rior to coding, Further gains are also achieved by modifying the quantizati on table used for coding the coefficients of the discrete cosine transform. Compared to standard JPEG, at the same level of reconstruction quality, th e new method can achieve compression ratio improvement by 13-161%, dependin g upon the context and the amount of cloud present in the specific image. T he results are demonstrated with the help of several real images obtained b y the University of Surrey, U.K,, satellites.