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Nonlinear unmixing of hyperspectral images using a generalized bilinear model [PDF]
, 2011 Nonlinear models have recently shown interesting properties for spectral unmixing. This paper studies a generalized bilinear model and a hierarchical Bayesian algorithm for unmixing hyperspectral images. The proposed model is a generalization not only of
Altmann, Yoann +9 more
core +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 This article proposed a novel spectral-spatial classification framework for hyperspectral image (HSI) through combining collaborative representation (CR) and maximum margin projection (MMP).
Haoyang Yu +6 more
doaj +1 more source
Hyperspectral Mamba for Hyperspectral Object Tracking
CoRRHyperspectral object tracking holds great promise due to the rich spectral information and fine-grained material distinctions in hyperspectral images, which are beneficial in challenging scenarios. While existing hyperspectral trackers have made progress by either transforming hyperspectral data into false-color images or incorporating modality fusion ...
Long Gao +4 more
openaire +2 more sources
Nature Communications, 2023 Hyperspectral imaging is vital for material identification but traditional systems are bulky, hindering the development of compact systems. While previous metasurfaces address volume issues, the requirements of complicated fabrication processes and ...
Chia-Hsiang Lin +3 more
semanticscholar +1 more source
En-Decoded Index Guided Edge Refinement Network for Change Detection of Remote Sensing Image
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingChange detection (CD) aims to analyze pairs of remote sensing images (RSIs) that are captured at different times to identify valuable information regarding changes in land features, which plays a crucial role in the fields of urban planning ...
Chunyan Yu +4 more
doaj +1 more source
Neighborhood Activity-Driven Representation for Hyperspectral Imagery Classification
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 In the classic sparse representation (SR)-based models and their improved versions with the spatial consistency, such as joint representation (JR)-based frameworks, the sparse coefficient is generally considered with the dictionary together for ...
Haoyang Yu +4 more
doaj +1 more source
Effective classification of Chinese tea samples in hyperspectral imaging
, 2013 Maximum likelihood and neural classifiers are two typical techniques in image classification. This paper investigates how to adapt these approaches to hyperspectral imaging for the classification of five kinds of Chinese tea samples, using visible light ...
Ren, Jinchang +2 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingHyperspectral remote sensing technology in wetland precise mapping plays a crucial role in ecological monitoring. Currently, hyperspectral image (HSI) wetland mapping achieves remarkable progress with the development of deep learning (DL) technology ...
Chunyan Yu +6 more
doaj +1 more source
Light: Science & Applications, 2023 We, for the first time, report the nanoscopic imaging study of anomalous infrared (IR) phonon enhancement of bilayer graphene, originated from the charge imbalance between the top and bottom layers, resulting in the enhancement of E1u mode of bilayer ...
Junghoon Jahng +8 more
doaj +1 more source
Endmember Estimation with Maximum Distance Analysis
Remote Sensing, 2021 Endmember estimation plays a key role in hyperspectral image unmixing, often requiring an estimation of the number of endmembers and extracting endmembers.
Xuanwen Tao +5 more
doaj +1 more source