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Lossless compression of hyperspectral imagery via RLS filter
Song, Jinwei; Zhang, Zhongwei; Chen, Xiaomin; Song, JW (reprint author), Chinese Acad Sci, Ctr Space Sci & Appl Res, Beijing 100190, Peoples R China.
Department空间技术部
Source PublicationELECTRONICS LETTERS
2013
Volume49Issue:16Pages:992-993
ISSN0013-5194
Language英语
AbstractA new algorithm for lossless compression of hyperspectral imagery is proposed. First, the average value of four neighbour pixels of the current pixel is calculated as local mean, which is subtracted by the current pixel to eliminate correlation in the current band image. The residual produced by this step is called local difference. The local differences of the pixels which co-locate with the current pixel in previous bands form the input vector of the recursive least square (RLS) filter, by which the prediction value of the current local difference is produced. Then, the prediction residual is sent to the adaptive arithmetic encoder. Experiment results show that the proposed algorithm produces state-of-the-art performance with relatively low complexity, and it is suitable for real-time compression on satellites.
Indexed BySCI
Document Type期刊论文
Identifierhttp://ir.nssc.ac.cn/handle/122/4950
Collection空间技术部
Corresponding AuthorSong, JW (reprint author), Chinese Acad Sci, Ctr Space Sci & Appl Res, Beijing 100190, Peoples R China.
Recommended Citation
GB/T 7714
Song, Jinwei,Zhang, Zhongwei,Chen, Xiaomin,et al. Lossless compression of hyperspectral imagery via RLS filter[J]. ELECTRONICS LETTERS,2013,49(16):992-993.
APA Song, Jinwei,Zhang, Zhongwei,Chen, Xiaomin,&Song, JW .(2013).Lossless compression of hyperspectral imagery via RLS filter.ELECTRONICS LETTERS,49(16),992-993.
MLA Song, Jinwei,et al."Lossless compression of hyperspectral imagery via RLS filter".ELECTRONICS LETTERS 49.16(2013):992-993.
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