FUSION OF MULTISPECTRAL AND SAR IMAGES USING SPARSE REPRESENTATION

被引：4

作者：

Zhang, Hai ^{[1
]}

Shen, Huanfeng ^{[1
]}

Zhang, Liangpei ^{[2
]}

机构：

[1] Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Peoples R China

[2] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan, Peoples R China

来源：

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

关键词：

Image fusion; Synthetic Aperture Radar; sparse representation; simultaneous orthogonal matching pursuit; INTEGRATION; WAVELET;

D O I：

10.1109/IGARSS.2016.7730878

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：

Complementary information from multi-sensor can be integrated to effectively solve many problems in remote sensing application. Synthetic Aperture Radar (SAR) imaging can be a feasible alternative to traditional optical remote sensing techniques because it is independent of solar illumination and weather conditions. This paper proposes a novel fusion framework combining IHS transform with sparse representation theory to fuse multispectral and SAR images. In addition, the simultaneous orthogonal matching pursuit (SOMP) technique is introduced to guarantee the efficiency. Experiments on various datasets have verified the effectiveness of proposed method.

引用

页码：7200 / 7203

页数：4

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