NSSC OpenIR  > 空间技术部
Lossless compression of hyperspectral imagery using a fast adaptive-length-prediction RLS filter
Song, Jinwei; Zhou, Li; Deng, Chao; An, Junshe
作者部门空间技术部
发表期刊REMOTE SENSING LETTERS
2019
卷号10期号:4页码:401-410
DOI10.1080/2150704X.2018.1562257
ISSN2150-704X
语种英语
摘要Recursive Least Square (RLS) filter has been applied to real-time lossless compression of hyperspectral imagery and been proved a high performance onboard algorithm. Recent research has revealed that the RLS filter with Adaptive-Length-Prediction (ALP) can significantly improve the compression performance. However, the prediction procedure with numerous bands slows down the run-time and is nearly impossible to be applied onboard. In this letter, we proposed a fast RLS algorithm which can accelerate the ALP stage by exploiting the feature of the projection matrix of the RLS algorithm. The experiment results illustrated that with the same compression ratio, the proposed algorithm is 100 times faster than the traditional RLS algorithm with ALP.
收录类别SCI
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文献类型期刊论文
条目标识符http://ir.nssc.ac.cn/handle/122/6674
专题空间技术部
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GB/T 7714
Song, Jinwei,Zhou, Li,Deng, Chao,et al. Lossless compression of hyperspectral imagery using a fast adaptive-length-prediction RLS filter[J]. REMOTE SENSING LETTERS,2019,10(4):401-410.
APA Song, Jinwei,Zhou, Li,Deng, Chao,&An, Junshe.(2019).Lossless compression of hyperspectral imagery using a fast adaptive-length-prediction RLS filter.REMOTE SENSING LETTERS,10(4),401-410.
MLA Song, Jinwei,et al."Lossless compression of hyperspectral imagery using a fast adaptive-length-prediction RLS filter".REMOTE SENSING LETTERS 10.4(2019):401-410.
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