%0 Journal Article
%T Denoising of hyperspectral remote sensing images using NSCT and KPCA<br>结合NSCT和KPCA的高光谱遥感图像去噪
%A WU Yiquan
%A WU Chao
%A <br>吴一全
%A 吴超
%J 遥感学报
%D 2012
%I 
%X As hyperspectral remote sensing image is easily interfered by noises, a denoising method of hyperspectral remote sensing image based on Nonsubsampled Contourlet Transform (NSCT) and Kernel Principal Component Analysis (KPCA) is proposed. First, hyperspectral image of each band is decomposed by NSCT to acquire the coefficients which are processed by KPCA. The proper principal components are selected for KPCA reconstruction according to noise features. Finally, the denoised image is obtained by performing inverse NSCT. Experimental results show that the proposed method can suppress noise interference in hyperspectral remote sensing images, and preserve the useful information of original data more completely.
%K hyperspectral remote sensing
%K image denoising
%K NSCT
%K KPCA<br>高光谱遥感
%K 图像去噪
%K 非下采样Contourlet变换
%K 核主成分分析
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=E62459D214FD64A3C8082E4ED1ABABED5711027BBBDDD35B&cid=A41A70F4AB56AB1B&jid=F926358B31AC94511E4382C083F7683C&aid=C8C3724E4E2B01E6105E93664948C47D&yid=99E9153A83D4CB11&vid=7801E6FC5AE9020C&iid=38B194292C032A66&sid=FF58680609C9D068&eid=B34BDD6A690A04C0&journal_id=1007-4619&journal_name=遥感学报&referenced_num=0&reference_num=16