In this paper, we develop a novel fusion method based on joint sparse-collaborative representation (SCR) for LS-HSI and HS-MSI.
Representation based methods to fuse a low spatial resolution hyperspectral image (LS-HSI) and a high spatial resolution multispectral image (HS-MSI) for ...
A novel single HS image SR approach is proposed based on a spatial correlation-regularized unmixing convolutional neural network (CNN), ...
Representation based methods to fuse a low spatial resolution hyperspectral image (LS-HSI) and a high spatial resolution multispectral image (HS-MSI) for ...
In this paper we apply the recently proposed J-SparseFI data fusion method to the fusion of a low-resolution hyperspectral image and a high-resolution ...
A novel algorithm that combines sparse and collaborative representation is proposed for target detection in hyperspectral imagery.
Missing: fuse | Show results with:fuse
In this paper, we propose to fuse HS and MS images within a constrained optimization framework, by incorporating a sparse regularization using dictionaries ...
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In this paper, we propose a coupled sparse tensor factorization (CSTF) based approach for fusing such images. In the proposed CSTF method, we consider an HR-HSI ...
Sep 19, 2014 · This paper presents a variational based approach to fusing hyperspectral and multispectral images. The fusion process is formulated as an inverse problem.
Missing: Joint collaborative
In this paper, we propose a non-negative structured sparse representation (NSSR) approach to recover a HR hyperspectral image from a LR hyperspectral image and ...