10 November 2007 A ROI-based deep space image compression algorithm
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Proceedings Volume 6795, Second International Conference on Space Information Technology; 679550 (2007) https://doi.org/10.1117/12.775009
Event: Second International Conference on Spatial Information Technology, 2007, Wuhan, China
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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Cuifang Zhao, Cuifang Zhao, Caicheng Shi, Caicheng Shi, Peikun He, Peikun He, Yinli Zhang, Yinli Zhang, } "A ROI-based deep space image compression algorithm", Proc. SPIE 6795, Second International Conference on Space Information Technology, 679550 (10 November 2007); doi: 10.1117/12.775009; https://doi.org/10.1117/12.775009

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