Hyperspectral and Multispectral Image Fusion Based on Spectral Matching in the Shearlet Domain

Abstract

In this paper, a new method for spatial resolution enhancement of hyperspectral images (HSI), based on the non-subsampled shearlet transform (NSST) is introduced. The proposed method integrates a high spectral resolution HSI with a high spatial resolution multispectral image (MSI) of the same scene. First, the HSI is spatially upsampled by means of a bicubic interpolation. Second, a 2D NSST is applied to each spectral band of the upsampled HSI and the MSI respectively. Third, the spectral coverage regions of HSI and MSI are matched and the detail shearlet coefficients of the HSI bands are replaced by detail shearlet information of the MSI, based on the spectral matching of both sensors. The proposed method is applied to real datasets and compared with some state-of-the-art fusion algorithms. The obtained results show that the proposed method significantly increases the spatial resolution while preserving the spectral content of the HSI.