Dec 20, 2019 · Fusion of hyperspectral and multispectral imagery data is utilized to reconstruct a super-resolution image with high spectral and spatial ...
Fusion of hyperspectral and multispectral imagery data is utilized to reconstruct a super-resolution image with high spectral and spatial resolution, ...
A proximal minimum-volume expression to regularize the convex simplex, enclosing all reconstructed image pixels instead of low-dimensional subspace data is ...
Dec 31, 2019 · The experimental tests suggest that the proposed method based on sparse and proximal regularization yields better performance than the benchmark.
We propose a novel HSI-MSI fusion method, named DDSSLR, which joins spatial-spectral dual-dictionary and structured sparse low-rank representation.
Oct 22, 2024 · In this paper, a new method for spatial resolution enhancement of a HSI using spectral unmixing and sparse coding (SUSC) is introduced. The ...
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: Proximal | Show results with:Proximal
People also ask
What are the growing applications of hyperspectral and multispectral imaging?
What is the difference between hyperspectral and multispectral images?
Which have more bands multispectral and hyperspectral?
Method: This paper proposes a non-locally centralized sparse representation model on a set of learned dictionaries to spatially regularize the fusion problem.
In this paper, we propose to fuse HS and MS images within a constrained optimization framework, by incorporating a sparse regularization using dictionaries ...
Fusion of Hyperspectral and Multispectral Images Using Spectral Unmixing and Sparse Coding · 61 Citations · 41 References.