[1]方凌江,粘永健,王迎春[].基于分类KLT的高光谱图像压缩[J].计算机技术与发展,2013,(11):82-85.
　FANG Ling-jiang[],NIAN Yong-jian[],WANG Ying-chun[].Hyperspectral Images Compression Based on Classified KLT[J].,2013,(11):82-85.
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基于分类KLT的高光谱图像压缩()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2013年11期
页码:
82-85
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
Hyperspectral Images Compression Based on Classified KLT
文章编号:
1673-629X（2013）11-0082-04
作者:
方凌江1; 粘永健1; 2; 王迎春[3]
[1]济南军区联勤部 指挥自动化工作站;[2]国防科技大学 电子科学与工程学院;[3]济南军区装备部 指挥自动化工作站
Author(s):
FANG Ling-jiang[1]; NIAN Yong-jian[1; 2]; WANG Ying-chun[3]
关键词:
高光谱图像; 数据压缩; 地物分类
Keywords:
hyperspectral images; data compression; ground classification
文献标志码:
A
摘要:
高光谱图像的有效压缩已经成为高光谱遥感领域研究的热点。提出了一种基于分类KLT( Karhunen-Loève Trans-form)的高光谱图像压缩算法。该算法利用光谱信息对高光谱图像进行地物分类，根据相邻波段的相关性对高光谱图像进行波段分组。在地物分类与波段分组的基础上，对每组的每一类地物数据分别进行 KL变换，利用 EBCOT ( Embedded Block Coding with Optimal Truncation)算法对所有主成分进行联合编码。实验结果表明，该算法能够取得优于JPEG2000以及DWT-JPEG2000的压缩性能，适合实现高光谱图像的有效压缩
Abstract:
Efficient compression of hyperspectral images has been the focus in the field of hyperspectral remote sensing. A new compres-sion algorithm of hyperspectral images based on classified-Karhunen-Loève Transform ( KLT) is proposed. Ground classification of hy-perspectral images is performed by using spectral information. Band grouping is carried out according to the correlation between adjacent two bands. Based on the ground classification and band grouping,KLT is performed on each ground class of hyperspectral images respec-tively in each group. EBCOT( Embedded Block Coding with Optimal Truncation) algorithm is used for the joint coding of all the princi-ple components. Experimental results show that the proposed algorithm can achieve better compression performance compared with those state-of-the-art compression algorithms such as JPEG2000 and DWT-JPEG2000,which is suitable for the efficient compression of hy-perspectral images

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更新日期/Last Update: 1900-01-01