CAJ | 학술논문

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。
고광보도상적유효압축이경성위고광보요감영역연구적열점。제출료일충기우분류KLT( Karhunen-Loève Trans-form)적고광보도상압축산법。해산법이용광보신식대고광보도상진행지물분류，근거상린파단적상관성대고광보도상진행파단분조。재지물분류여파단분조적기출상，대매조적매일류지물수거분별진행 KL변환，이용 EBCOT ( Embedded Block Coding with Optimal Truncation)산법대소유주성분진행연합편마。실험결과표명，해산법능구취득우우JPEG2000이급DWT-JPEG2000적압축성능，괄합실현고광보도상적유효압축。
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.