Spectral Modulation for Fusion of Hyperspectral and Multispectral Images

Abstract

Hyperspectral (HS) and multispectral (MS) image fusion has attracted great attention during the past decades. Numerous of fusion methods have been developed and shown their effectiveness particularly on simulated data. Nonetheless, for real remote sensing data, the different acquisition times or conditions result in a serious spectral distortion and severely affect the fusion quality. Yet very few works have considered this issue. In this paper, a spectral modulation (SM) method is proposed to better maintain the spectral information of the HS data when fusing with MS data. The goal is to generate an adjusted MS image that would have been observed under the same imaging conditions with the corresponding HS sensor. Experiments on two HS and MS data sets acquired by different platforms demonstrate that the proposed method is beneficial to the spectral fidelity and spatial enhancement of the fused image compared with some state-of-the-art fusion techniques.