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.
['Hai Zhang', 'Huanfeng Shen', 'Liangpei Zhang']
Fusion of multispectral and SAR images using sparse representation