一种空谱联合预测的高光谱图像无损压缩方法
史泽林; 陈永红; 罗海波
2010-11-10
专利国别中国
专利号CN101883274A
专利类型发明
产权排序1
权利人中国科学院沈阳自动化研究所
其他题名Spatial-spectral associated prediction-based hyperspectral image lossless compression method
中文摘要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。
是否PCT专利
英文摘要The 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]

公开日期2013-05-22
申请日期2009-05-08
语种中文
专利申请号CN200910011461.8
专利代理沈阳科苑专利商标代理有限公司 21002
内容类型专利
源URL[http://ir.sia.ac.cn/handle/173321/13218]  
专题沈阳自动化研究所_自动化系统研究室
推荐引用方式
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. CN101883274A. 2010-11-10.
个性服务
查看访问统计
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。


©版权所有 ©2017 CSpace - Powered by CSpace