A ROI-based deep space image compression algorithm

In order to satisfy the requirement of bandwidth and storage capacity, high efficient image compression coding method is one of the key technologies. The general image compression methods only encode the original pixels without any analysis. A deep space image compression algorithm based on the region of interest (ROI) is proposed in the paper. For deep space exploration, only parts of the image are interested in depending on the application background. Some image area such as secondary planet, star and satellite can be considered as ROI. The proposed method includes image segmentation and different image compressions for different regions. The algorithm is characterized with higher image signal noise ratio (ISNR) of the reconstructed image and lower computation complexity, and the image detail preserving capability of the algorithm is better than that of JPEG2000. Because of its simplicity, fastness, and small storage, the algorithm is easy to be realized in hardware and suitable for space borne application.