Pure endmember extraction using robust kernel archetypoid analysis for hyperspectral imagery
Sign Up to like & getrecommendations! Published in 2017 at "Isprs Journal of Photogrammetry and Remote Sensing"
DOI: 10.1016/j.isprsjprs.2017.08.001
Abstract: Abstract A robust kernel archetypoid analysis (RKADA) method is proposed to extract pure endmembers from hyperspectral imagery (HSI). The RKADA assumes that each pixel is a sparse linear mixture of all endmembers and each endmember… read more here.
Keywords: analysis; robust kernel; endmember extraction; pure endmember ... See more keywords
Hybrid Preprocessing Algorithm for Endmember Extraction Using Clustering, Over-Segmentation, and Local Entropy Criterion
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2017.2694439
Abstract: Most spectral mixture analyses in the literature overlook the spatial correlation of neighborhood pixels. The main contribution of this paper is to consider the impacts of both spatial and spectral information prior to endmember (EM)… read more here.
Keywords: extraction; entropy criterion; segmentation; endmember extraction ... See more keywords
Spatial-Spectral Hyperspectral Endmember Extraction Using a Spatial Energy Prior Constrained Maximum Simplex Volume Approach
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2020.2981402
Abstract: Endmember extraction algorithms (EEAs) are among the most commonly discussed types of hyperspectral image processing in the past three decades. This article proposes a spatial energy prior constrained maximum simplex volume (SENMAV) approach for spatial-spectral… read more here.
Keywords: endmember extraction; spatial energy; spatial spectral; energy prior ... See more keywords
Endmember Extraction From Hyperspectral Imagery Based on Probabilistic Tensor Moments
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2019.2963114
Abstract: This letter presents a novel hyperspectral endmember extraction approach that integrates a tensor-based decomposition scheme with a probabilistic framework in order to take advantage of both technologies when uncovering the signatures of pure spectral constituents… read more here.
Keywords: tensor; decomposition; endmember extraction; probabilistic tensor ... See more keywords
EndNet: Sparse AutoEncoder Network for Endmember Extraction and Hyperspectral Unmixing
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2018.2856929
Abstract: Data acquired from multichannel sensors are a highly valuable asset to interpret the environment for a variety of remote sensing applications. However, low spatial resolution is a critical limitation for previous sensors, and the constituent… read more here.
Keywords: extraction hyperspectral; hyperspectral unmixing; endmember extraction; autoencoder ... See more keywords
A Global-to-Local Evolutionary Algorithm for Hyperspectral Endmember Extraction
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3242364
Abstract: Recently, evolutionary algorithms (EAs) have shown their promising performance in solving the hyperspectral endmember extraction (EE) task. Despite that, most of the existing EA-based EE algorithms mainly take advantage of the global search capability of… read more here.
Keywords: hyperspectral endmember; global local; endmember extraction; search ... See more keywords
An Optimization Method for Hyperspectral Endmember Extraction Based on K-SVD
Sign Up to like & getrecommendations! Published in 2019 at "Photogrammetric Engineering and Remote Sensing"
DOI: 10.14358/pers.85.12.879
Abstract: Mixed pixels are common in hyperspectral imagery (HSI). Due to the complexity of the ground object distribution, some end-member extraction methods cannot obtain good results and the processes are complex. Therefore, this paper proposes an… read more here.
Keywords: extraction; optimization method; endmember extraction; method ... See more keywords