Results 41 to 50 of about 1,956 (163)
A Hierarchical Sparsity Unmixing Method to Address Endmember Variability in Hyperspectral Image
Remote Sensing, 2018 With a low spectral resolution hyperspectral sensor, the signal recorded from a given pixel against the complex background is a mixture of spectral contents. To improve the accuracy of classification and subpixel object detection, hyperspectral unmixing (
Jinlin Zou, Jinhui Lan, Yang Shao
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Hyperspectral unmixing (HU) has become an important technique in exploiting hyperspectral data since it decomposes a mixed pixel into a collection of endmembers weighted by fractional abundances.
E. M. M. B. Ekanayake +7 more
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Deep convolutional transformer network for hyperspectral unmixing
European Journal of Remote Sensing, 2023 Hyperspectral unmixing (HU) is considered one of the most important ways to improve hyperspectral image analysis. HU aims to break down the mixed pixel into a set of spectral signatures, often commonly referred to as endmembers, and determine the ...
Fazal Hadi +3 more
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Spectral unmixing of Multispectral Lidar signals [PDF]
, 2015 In this paper, we present a Bayesian approach for spectral unmixing of multispectral Lidar (MSL) data associated with surface reflection from targeted surfaces composed of several known materials.
Altmann, Yoann +2 more
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Hyperspectral Unmixing Using Robust Deep Nonnegative Matrix Factorization
Remote Sensing, 2023 Nonnegative matrix factorization (NMF) and its numerous variants have been extensively studied and used in hyperspectral unmixing (HU). With the aid of the designed deep structure, deep NMF-based methods demonstrate advantages in exploring the ...
Risheng Huang +4 more
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Hyperspectral reflectance spectra of floating matters derived from Hyperspectral Imager for the Coastal Ocean (HICO) observations [PDF]
Earth System Science Data, 2022 Using data collected by the Hyperspectral Imager for the Coastal Ocean (HICO) on the International Space Station between 2010–2014, hyperspectral reflectance spectra of various floating matters in global oceans and lakes are derived for the spectral ...
C. Hu
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Gradients in urban material composition: A new concept to map cities with spaceborne imaging spectroscopy data [PDF]
, 2019 To understand processes in urban environments, such as urban energy fluxes or surface temperature patterns, it is important to map urban surface materials. Airborne imaging spectroscopy data have been successfully used to identify urban surface materials
Feilhauer, Hannes +3 more
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Hyperspectral Unmixing Based on Dual-Depth Sparse Probabilistic Latent Semantic Analysis [PDF]
, 2018 This paper presents a novel approach for spectral unmixing of remotely sensed hyperspectral data. It exploits probabilistic latent topics in order to take advantage of the semantics pervading the latent topic space when identifying spectral signatures ...
Fernandez-Beltran, Ruben +3 more
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Spectral Unmixing via Data-guided Sparsity
, 2014 Hyperspectral unmixing, the process of estimating a common set of spectral bases and their corresponding composite percentages at each pixel, is an important task for hyperspectral analysis, visualization and understanding.
Fan, Bin +5 more
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Nonlinear unmixing of hyperspectral images: Models and algorithms [PDF]
, 2013 When considering the problem of unmixing hyperspectral images, most of the literature in the geoscience and image processing areas relies on the widely used linear mixing model (LMM).
Bermudez, José Carlos Moreira +5 more
core +8 more sources