Sparsity Constrained Fusion of Hyperspectral and Multispectral Images [PDF]
, 2022 Fusing a Hyperspectral image (HSI) and a multispectral image (MSI) from different sensors is an economic and effective approach to get an image with both high spatial and spectral resolution, but localized changes between the multiplatform images can ...
Jia, Sen +4 more
core +1 more source
Thangka Hyperspectral Image Super-Resolution Based on a Spatial–Spectral Integration Network
Remote Sensing, 2023 Thangka refers to a form of Tibetan Buddhist painting on a fabric, scroll, or Thangka, often depicting deities, scenes, or mandalas. Deep-learning-based super-resolution techniques have been applied to improve the spatial resolution of hyperspectral ...
Sai Wang, Fenglei Fan
doaj +1 more source
A Bipartite Graph Partition-Based Coclustering Approach With Graph Nonnegative Matrix Factorization for Large Hyperspectral Images [PDF]
, 2022 International audienceClustering large hyperspectral images (HSIs) is a very challenging problem because large HSIs have high dimensionality, large spectral variability, and large computational and memory consumption. Recently, sparse subspace clustering
Xiao, Liang +3 more
core +1 more source
A new HSI denoising method via interpolated block matching 3D and guided filter [PDF]
PeerJ, 2021 A new hyperspectral images (HSIs) denoising method via Interpolated Block-Matching and 3D filtering and Guided Filtering (IBM3DGF) denoising method is proposed.
Ping Xu +4 more
doaj +2 more sources
Remote Sensing, 2023 Hyperspectral images (HSIs) are widely used to identify and characterize objects in scenes of interest, but they are associated with high acquisition costs and low spatial resolutions.
Liyao Song +6 more
doaj +1 more source
MFFCG – Multi feature fusion for hyperspectral image classification using graph attention network [PDF]
, 2023 Classification methods that are based on hyperspectral images (HSIs) are playing an increasingly significant role in the processes of target detection, environmental management, and mineral mapping as a result of the fast development of hyperspectral ...
Wu, Guilu +7 more
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Hyperspectral Image Super-Resolution Algorithm Based on Graph Regular Tensor Ring Decomposition
Remote Sensing, 2023 This paper introduces a novel hyperspectral image super-resolution algorithm based on graph-regularized tensor ring decomposition aimed at resolving the challenges of hyperspectral image super-resolution.
Shasha Sun +5 more
doaj +1 more source
Intraoperative reperfusion assessment of human pancreas allografts using hyperspectral imaging (HSI) [PDF]
Hepatobiliary Surgery and Nutrition, 2022 The most common causes of early graft loss in pancreas transplantation are insufficient blood supply and leakage of the intestinal anastomosis. Therefore, it is critical to monitor graft perfusion and oxygenation during the early post-transplant period. The goal of our pilot study was to evaluate the utility of hyperspectral imaging (HSI) in monitoring
Robert, Sucher +9 more
openaire +2 more sources
S 2 DMSC: A Self-Supervised Deep Multilevel Subspace Clustering Approach for Large Hyperspectral Images [PDF]
, 2023 International audienceSubspace clustering (SC) has achieved remarkable success in hyperspectral images (HSIs) due to the powerful representation ability of handling high-dimensional complex data.
Xiao, Liang +3 more
core +1 more source
Spectral unmixing of hyperspectral images based on block sparse structure [PDF]
, 2023 Spectral unmixing (SU) of hyperspectral images (HSIs) is one of the important areas in remote sensing (RS) that needs to be carefully addressed in different RS applications.
Azarang S. H. M. +3 more
core +1 more source