计算机技术与发展Issue(11)：82-85,90,5.DOI:10.3969/j.issn.1673-629X.2013.11.021
基于分类KLT的高光谱图像压缩
Hyperspectral Images Compression Based on Classified KLT
摘要
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.关键词
高光谱图像/数据压缩/地物分类Key words
hyperspectral images/data compression/ground classification分类
信息技术与安全科学引用本文复制引用
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):82-85,90,5.基金项目
国家自然科学基金资助项目(41201363) （41201363）
湖南省自然科学基金资助项目(11JJ3066) （11JJ3066）
