Results 51 to 60 of about 77,969 (223)
An Overview on Linear Unmixing of Hyperspectral Data [PDF]
Mathematical Problems in Engineering, 2020 Hyperspectral remote sensing technology has a strong capability for ground object detection due to the low spatial resolution of hyperspectral imaging spectrometers. A single pixel that leads to a hyperspectral remote sensing image usually contains more than one feature coverage type, resulting in a mixed pixel.
Jiaojiao Wei, Xiaofei Wang
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Pixel-Level and Global Similarity-Based Adversarial Autoencoder Network for Hyperspectral Unmixing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingHyperspectral unmixing is a critical task in remote sensing, enabling the decomposition of hyperspectral data into their constituent endmembers and abundances.
Wei Tao +5 more
doaj +1 more source
Blind Hyperspectral Unmixing with Enhanced 2DTV Regularization Term
Remote Sensing, 2023 For the problem where the existing hyperspectral unmixing methods do not take full advantage of the correlations and differences between all these bands, resulting in affecting the final unmixing results, we design an enhanced 2DTV (E-2DTV ...
Peng Wang +4 more
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Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Advanced Intelligent Discovery, EarlyView.Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
wiley +1 more source
Hyperspectral Image Resolution Enhancement Based on Spectral Unmixing and Information Fusion [PDF]
, 2011 Hyperspectral imaging sensors exibit high spectral resolution, but normally low spatial resolution. This leads to spectral signatures of pixels originating from different object types. Such pixels are called mixed pixels.
Avbelj, Janja +4 more
core
Bayesian separation of spectral sources under non-negativity and full additivity constraints [PDF]
, 2009 This paper studied Bayesian algorithms for separating linear mixtures of spectral sources under non-negativity and full additivity constraints. These two constraints are required in some applications such as hyperspectral imaging and spectroscopy to get ...
Moussaoui, Saïd +3 more
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Remote Sensing, 2023 Spectral unmixing is one of the prime topics in hyperspectral image analysis, as images often contain multiple sources of spectra. Spectral variability is one of the key factors affecting unmixing accuracy, since spectral signatures are affected by ...
Ying Cheng +3 more
doaj +1 more source
Remote Sensing in Ecology and Conservation, EarlyView.We demonstrate that high‐resolution multispectral imagery combined with machine learning can accurately predict key biocrust functional indicators, particularly the UV‐protective pigment scytonemin, across dryland ecosystems. Using fine‐scale imagery acquired in the Chihuahuan Desert and Colorado Plateau, we identified spectral bands strongly ...
Raúl Román +8 more
wiley +1 more source
NMF-SAE: An Interpretable Sparse Autoencoder for Hyperspectral Unmixing
, 2021 Hyperspectral unmixing is an important tool to learn the material constitution and distribution of a scene. Model-based unmixing methods depend on well-designed iterative optimization algorithms, which is usually time consuming.
Jun Zhou +9 more
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Seeded Growth of Plasmonic Core‐Shell NU‐1000 NanoMOFs With Intracellular Optical Readout
Small, EarlyView.Seed‐mediated growth yields plasmonic core‐shell nanocomposites by encapsulating gold nanoparticles within NU‐1000 nanoMOFs, preserving morphology and optical response. The materials exhibit tunable photoluminescence quenching, efficient photothermal heating, and SERS activity.
Manuel Ceballos +9 more
wiley +1 more source