Hyperspectral and Multispectral Image Fusion based on a Sparse Representation

by   Qi Wei, et al.

This paper presents a variational based approach to fusing hyperspectral and multispectral images. The fusion process is formulated as an inverse problem whose solution is the target image assumed to live in a much lower dimensional subspace. A sparse regularization term is carefully designed, relying on a decomposition of the scene on a set of dictionaries. The dictionary atoms and the corresponding supports of active coding coefficients are learned from the observed images. Then, conditionally on these dictionaries and supports, the fusion problem is solved via alternating optimization with respect to the target image (using the alternating direction method of multipliers) and the coding coefficients. Simulation results demonstrate the efficiency of the proposed algorithm when compared with the state-of-the-art fusion methods.


page 14

page 17

page 19

page 21


A Dual Symmetric Gauss-Seidel Alternating Direction Method of Multipliers for Hyperspectral Sparse Unmixing

Since sparse unmixing has emerged as a promising approach to hyperspectr...

Hyperspectral-Multispectral Image Fusion with Weighted LASSO

Spectral imaging enables spatially-resolved identification of materials ...

Subspace-Based Feature Fusion From Hyperspectral And Multispectral Image For Land Cover Classification

In remote sensing, hyperspectral (HS) and multispectral (MS) image fusio...

Fusing Multiple Multiband Images

We consider the problem of fusing an arbitrary number of multiband, i.e....

Patch-based Sparse Representation For Bacterial Detection

In this paper, we propose a supervised approach for bacterial detection ...

Convolutional Simultaneous Sparse Approximation with Applications to RGB-NIR Image Fusion

Simultaneous sparse approximation (SSA) seeks to represent a set of depe...

Visual Tracking via Nonnegative Regularization Multiple Locality Coding

This paper presents a novel object tracking method based on approximated...

Please sign up or login with your details

Forgot password? Click here to reset