MULTI-WAY PROJECTIONS-BASED RECONSTRUCTION FOR HYPERSPECTRAL IMAGE DENOISING

被引：0

作者：

He, Zhi ^{[1
]}

Zhou, Wei ^{[1
]}

Li, Jun ^{[1
]}

Liu, Lin ^{[1
,2
]}

机构：

[1] Sun Yat Sen Univ, Ctr Integrated Geog Informat Anal, Sch Geog & Planning, Guangdong Prov Key Lab Urbanizat & Geosimulat, Guangzhou 510275, Guangdong, Peoples R China

[2] Univ Cincinnati, Dept Geog, Cincinnati, OH 45221 USA

来源：

2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2016年

基金：

中国国家自然科学基金; 国家高技术研究发展计划(863计划);

关键词：

Hyperspectral image (HSI); noise reduction; compressed sensing (CS); low-rank tensor approximation; multi-way analysis; NOISE; REDUCTION;

D O I：

10.1109/IGARSS.2016.7729752

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, we propose a multi-way projections-based reconstruction method for noise reduction of hyperspectral image (HSI). Core ideas of the proposed method are twofold: 1) the original HSI is partitioned into many small three-dimensional (3D) patches. Each of the patch is taken as a third-order tensor, on which compressive multi-way measurements are performed; 2) de noised patches are produced by the approximate low multilinear-rank reconstructions, and the final denoised HSI can be obtained by putting the denoised patches back to where they are in the original HSI. Experiments conducted on the real hyperspectral data set demonstrate the promising performance of the proposed method.

引用

页码：2913 / 2916

页数：4

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