Coupled Tensor Decomposition for Hyperspectral Pansharpening

Abstract

This paper aims to effectively preserve the spatial and spectral information of hyperspectral (HS) images. For this purpose, the author proposed a new image fusion method based on coupled tensor decomposition (CTD). First, the wanted high spatial resolution HS (HRHS) images were decomposed into the core tensor and basis matrices. Assuming that the basis matrices can be calculated from low spatial resolution HS (LRHS) images, the core tensor was estimated from the high spatial resolution multispectral (HRMS) images based on the relationship between HRHS and HRMS images. Finally, the HRHS images were obtained by reconstructing the core tensor with basis matrices. Owing to the good properties of tensor, the proposed method achieved better fusion results on different data sets than those of the contrastive methods. The research findings shed new light on hyperspectral pansharpening.