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Proceedings Paper

A ROI-based deep space image compression algorithm
Author(s): Cuifang Zhao; Caicheng Shi; Peikun He; Yinli Zhang
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Paper Abstract

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.

Paper Details

Date Published: 10 November 2007
PDF: 5 pages
Proc. SPIE 6795, Second International Conference on Space Information Technology, 679550 (10 November 2007); doi: 10.1117/12.775009
Show Author Affiliations
Cuifang Zhao, Beijing Institute of Technology (China)
Zhejiang Normal Univ. (China)
Caicheng Shi, Beijing Institute of Technology (China)
Peikun He, Beijing Institute of Technology (China)
Yinli Zhang, Hengyan Radio Television Univ. (China)

Published in SPIE Proceedings Vol. 6795:
Second International Conference on Space Information Technology
Cheng Wang; Shan Zhong; Jiaolong Wei, Editor(s)

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