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一种空谱联合预测的高光谱图像无损压缩方法
Alternative TitleSpatial-spectral associated prediction-based hyperspectral image lossless compression method
史泽林; 陈永红; 罗海波
Department自动化系统研究室
Rights Holder中国科学院沈阳自动化研究所
Patent Agent沈阳科苑专利商标代理有限公司 21002
Country中国
Subtype发明授权
Status有权
Abstract本发明涉及一种空谱联合预测的高光谱图像无损压缩方法,包括以下步骤:根据谱间相关系数的大小,对输入高光谱图像进行波段组合;根据不同的波段组合选择相应的预测算法消除相关性,得到差值图像;对差值图像进行RICE熵编码,得到压缩码流,进行存储或传输,在本地或异地实现可逆解码。本发明方法可有效地降低整幅图像的空谱冗余,减少了编码计算量,整个编码过程不会丢失任何信息,实现了无损压缩,提高了高光谱图像的无损压缩比,降低存储图像所需的存储资源,减轻了传输带宽负担,编码复杂度低,易于硬件实现和实时传输,并具有较好的抗误码能力。
Other AbstractThe invention relates to a spatial-spectral associated prediction-based hyperspectral image lossless compression method, which comprises the following steps: conducting band combination to input hyperspectral images according to the magnitude of a spectrum correlation coefficient; selecting corresponding prediction algorithms according to different band combinations to eliminate correlation and to obtain a difference image; and conducting RICE entropy coding to the difference image to obtain a compressed code stream, storing or transmitting the compressed code stream and realizing reversible decoding locally or at other places. By adopting the method, the invention has the advantages that the spatial-spectral redundancy of the entire image can be effectively reduced, the calculated amountfor coding is reduced, no information is lost in the entire coding process, the lossless compression is realized, the lossless compression ratio of the hyperspectral image is improved, the storage resource required for image storage is reduced, the transmission bandwidth burden is reduced, the coding complexity is low, the hardware realization and the real-time transmission are facilitated and the error resilience is good.

[en;CN101883274A]

PCT Attributes
Application Date2009-05-08
2010-11-10
Date Available2013-05-22
Application NumberCN200910011461.8
Open (Notice) NumberCN101883274B
Language中文
Contribution Rank1
Document Type专利
Identifierhttp://ir.sia.cn/handle/173321/14329
Collection自动化系统研究室
Affiliation中国科学院沈阳自动化研究所
Recommended Citation
GB/T 7714
史泽林,陈永红,罗海波. 一种空谱联合预测的高光谱图像无损压缩方法[P]. 2010-11-10.
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