Rashed, T.[Tarek],
Weeks, J.R.[John R.],
Roberts, D.A.[Dar A.],
Rogan, J.[John],
Powell, R.[Rebecca],
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WWW Link.
0309
The results showed that a majority of the image could be modeled
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1003
Impervious surface area; Spectral mixture analysis; Endmember
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0611
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1303
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1103
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1107
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1112
BibRef
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1112
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GeoRS(49), No. 11, November 2011, pp. 4223-4238.
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1112
BibRef
Chan, T.H.[Tsung-Han],
Ma, W.K.[Wing-Kin],
Ambikapathi, A.,
Chi, C.Y.[Chong-Yung],
A Simplex Volume Maximization Framework for Hyperspectral Endmember
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GeoRS(49), No. 11, November 2011, pp. 4177-4193.
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1112
BibRef
Chan, T.H.,
Ambikapathi, A.,
Ma, W.K.,
Chi, C.Y.,
Robust Affine Set Fitting and Fast Simplex Volume Max-Min for
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IEEE DOI Data mining; ;Noise; Robustness; Alternating optimization;
robust dimension reduction; simplex volume max-min; successive optimization
1307
BibRef
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A New Maximum Simplex Volume Method Based on Householder Transformation
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GeoRS(50), No. 1, January 2012, pp. 104-118.
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1201
BibRef
Geng, X.R.[Xiu-Rui],
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Zhao, Y.C.[Yong-Chao],
Wang, F.X.[Fu-Xiang],
A Gaussian elimination based fast endmember extraction algorithm for
hyperspectral imagery,
PandRS(79), No. 1, May 2013, pp. 211-218.
Elsevier DOI
1305
Hyperspectral data; Endmember; Gaussian elimination; Simplex
BibRef
Geng, X.R.[Xiu-Rui],
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Clever eye algorithm for target detection of remote sensing imagery,
PandRS(114), No. 1, 2016, pp. 32-39.
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1604
Hyperspectral data
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An endmember-based distance for content based hyperspectral image
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PR(45), No. 9, September 2012, pp. 3472-3489.
Elsevier DOI
1206
Hyperspectral images; Content based image retrieval; Endmember
induction algorithm; Image similarity
BibRef
Veganzones, M.A.[Miguel A.],
Datcu, M.[Mihai],
Graña, M.[Manuel],
Further results on dissimilarity spaces for hyperspectral images
RF-CBIR,
PRL(34), No. 14, 2013, pp. 1659-1668.
Elsevier DOI
1308
Hyperspectral imaging
BibRef
Ambikapathi, A.,
Chan, T.H.,
Chi, C.Y.,
Keizer, K.,
Hyperspectral Data Geometry-Based Estimation of Number of Endmembers
Using p-Norm-Based Pure Pixel Identification Algorithm,
GeoRS(51), No. 5, May 2013, pp. 2753-2769.
IEEE DOI
1305
BibRef
Thompson, D.R.,
Bornstein, B.J.,
Chien, S.A.,
Schaffer, S.,
Tran, D.,
Bue, B.D.,
Castano, R.,
Gleeson, D.F.,
Noell, A.,
Autonomous Spectral Discovery and Mapping Onboard the EO-1 Spacecraft,
GeoRS(51), No. 6, 2013, pp. 3567-3579.
IEEE DOI
1307
hyperspectral imaging; Endmember detection;
BibRef
Zhang, A.B.[An-Bing],
Xie, Y.C.[Yi-Chun],
Chaos Theory-Based Data-Mining Technique for Image Endmember
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GeoRS(52), No. 4, April 2014, pp. 1935-1947.
IEEE DOI
1403
Lyapunov methods
BibRef
Li, W.L.[Wen-Liang],
Wu, C.S.[Chang-Shan],
Incorporating land use land cover probability information into
endmember class selections for temporal mixture analysis,
PandRS(101), No. 1, 2015, pp. 163-173.
Elsevier DOI
1503
Logistic regression
BibRef
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Shi, J.C.[Jian-Cheng],
Du, J.Y.[Jin-Yang],
An Improved Endmember Selection Method Based on Vector Length for
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RS(7), No. 5, 2015, pp. 6280-6295.
DOI Link
1506
BibRef
Jiao, C.Z.[Chang-Zhe],
Zare, A.[Alina],
Functions of Multiple Instances for Learning Target Signatures,
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1506
Approximation algorithms
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Zare, A.[Alina],
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Glenn, T.[Taylor],
Discriminative Multiple Instance Hyperspectral Target
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PAMI(40), No. 10, October 2018, pp. 2342-2354.
IEEE DOI
1809
Training data, Hyperspectral imaging, Detectors, Dictionaries,
Object detection, Training, Global Positioning System,
multiple instance
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Jiao, C.Z.[Chang-Zhe],
Zare, A.[Alina],
Multiple Instance Dictionary Learning using Functions of Multiple
Instances,
ICPR16(2688-2693)
IEEE DOI
1705
Dictionaries, Face, Face recognition, Learning systems,
Object detection, Training, Training, data
BibRef
Zare, A.[Alina],
Gader, P.D.[Paul D.],
Pattern Recognition Using Functions of Multiple Instances,
ICPR10(1092-1095).
IEEE DOI
1008
BibRef
Zare, A.[Alina],
Gader, P.D.[Paul D.],
Endmember detection using the Dirichlet process,
ICPR08(1-4).
IEEE DOI
0812
feature reduction for hyperspectral data
BibRef
Geng, X.R.[Xiu-Rui],
Sun, K.[Kang],
Ji, L.[Luyan],
Zhao, Y.C.[Yong-Chao],
Tang, H.R.[Hai-Rong],
Optimizing the Endmembers Using Volume Invariant Constrained Model,
IP(24), No. 11, November 2015, pp. 3441-3449.
IEEE DOI
1509
hyperspectral imaging
BibRef
Geng, X.R.[Xiu-Rui],
Tang, H.R.[Hai-Rong],
Clustering by connection center evolution,
PR(98), 2020, pp. 107063.
Elsevier DOI
1911
Clustering center, Clustering, Connected graph, Connectivity
BibRef
Deng, Y.B.[Ying-Bin],
Wu, C.S.[Chang-Shan],
Development of a Class-Based Multiple Endmember Spectral Mixture
Analysis (C-MESMA) Approach for Analyzing Urban Environments,
RS(8), No. 4, 2016, pp. 349.
DOI Link
1604
BibRef
Li, H.C.,
Chang, C.I.,
Recursive Orthogonal Projection-Based Simplex Growing Algorithm,
GeoRS(54), No. 7, July 2016, pp. 3780-3793.
IEEE DOI
1606
Algorithm design and analysis
BibRef
Geng, X.,
Ji, L.,
Wang, F.,
Zhao, Y.,
Gong, P.,
Statistical Volume Analysis: A New Endmember Extraction Method for
Multi/Hyperspectral Imagery,
GeoRS(54), No. 10, October 2016, pp. 6100-6109.
IEEE DOI
1610
feature extraction
BibRef
Zhang, C.Y.[Cheng-Ye],
Qin, Q.M.[Qi-Ming],
Zhang, T.Y.[Tian-Yuan],
Sun, Y.H.[Yuan-Heng],
Chen, C.[Chao],
Endmember extraction from hyperspectral image based on discrete
firefly algorithm (EE-DFA),
PandRS(126), No. 1, 2017, pp. 108-119.
Elsevier DOI
1704
Endmember extraction
BibRef
Xu, M.M.[Ming-Ming],
Zhang, L.P.[Liang-Pei],
Du, B.[Bo],
Zhang, L.[Lefei],
Fan, Y.G.[Yan-Guo],
Song, D.M.[Dong-Mei],
A Mutation Operator Accelerated Quantum-Behaved Particle Swarm
Optimization Algorithm for Hyperspectral Endmember Extraction,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link
1704
BibRef
Heylen, R.,
Parente, M.,
Scheunders, P.,
Estimation of the Number of Endmembers in a Hyperspectral Image via
the Hubness Phenomenon,
GeoRS(55), No. 4, April 2017, pp. 2191-2200.
IEEE DOI
1704
data handling
BibRef
Sun, W.W.[Wei-Wei],
Ma, J.[Jun],
Yang, G.[Gang],
Du, B.[Bo],
Zhang, L.P.[Liang-Pei],
A Poisson nonnegative matrix factorization method with parameter
subspace clustering constraint for endmember extraction in
hyperspectral imagery,
PandRS(128), No. 1, 2017, pp. 27-39.
Elsevier DOI
1706
Endmember, extraction
BibRef
Itoh, Y.,
Feng, S.,
Duarte, M.F.,
Parente, M.,
Semisupervised Endmember Identification in Nonlinear Spectral
Mixtures via Semantic Representation,
GeoRS(55), No. 6, June 2017, pp. 3272-3286.
IEEE DOI
1706
Feature extraction, Hidden Markov models, Hyperspectral imaging,
Libraries, Semantics, Wavelet transforms,
hyperspectral image (HSI), nonlinear mixing, semantics, unmixing, wavelet
BibRef
Liu, R.[Rong],
Du, B.[Bo],
Zhang, L.P.[Liang-Pei],
Multiobjective Optimized Endmember Extraction for Hyperspectral Image,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link
1706
BibRef
Cui, C.[Can],
Li, Y.[Ying],
Liu, B.X.[Bing-Xin],
Li, G.[Guannan],
A New Endmember Preprocessing Method for the Hyperspectral Unmixing
of Imagery Containing Marine Oil Spills,
IJGI(6), No. 9, 2017, pp. xx-yy.
DOI Link
1710
BibRef
Li, H.L.[Hua-Li],
Liu, J.[Jun],
Yu, H.C.[Hai-Cong],
An Automatic Sparse Pruning Endmember Extraction Algorithm with a
Combined Minimum Volume and Deviation Constraint,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link
1805
BibRef
Zou, J.L.[Jin-Lin],
Lan, J.H.[Jin-Hui],
Shao, Y.[Yang],
A Hierarchical Sparsity Unmixing Method to Address Endmember
Variability in Hyperspectral Image,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link
1806
BibRef
Wang, X.Y.[Xin-Yu],
Zhong, Y.F.[Yan-Fei],
Xu, Y.,
Zhang, L.P.[Liang-Pei],
Xu, Y.Y.[Yan-Yan],
Saliency-Based Endmember Detection for Hyperspectral Imagery,
GeoRS(56), No. 7, July 2018, pp. 3667-3680.
IEEE DOI
1807
hyperspectral imaging, image reconstruction, object detection,
Saliency-based endmember detection, abundance anomalies,
visual saliency
BibRef
Wang, X.Y.[Xin-Yu],
Zhong, Y.F.[Yan-Fei],
Cui, C.Y.[Chun-Yang],
Zhang, L.P.[Liang-Pei],
Xu, Y.Y.[Yan-Yan], i
Autonomous Endmember Detection via an Abundance Anomaly Guided
Saliency Prior for Hyperspectral Imagery,
GeoRS(59), No. 3, March 2021, pp. 2336-2351.
IEEE DOI
2103
Estimation, Hyperspectral imaging, SPICE, Visualization, Correlation,
Abundance anomaly (AA), endmember extraction (EE),
virtual dimensionality (VD)
BibRef
Jiao, C.Z.[Chang-Zhe],
Chen, C.[Chao],
McGarvey, R.G.[Ronald G.],
Bohlman, S.[Stephanie],
Jiao, L.C.[Li-Cheng],
Zare, A.[Alina],
Multiple instance hybrid estimator for hyperspectral target
characterization and sub-pixel target detection,
PandRS(146), 2018, pp. 235-250.
Elsevier DOI
1812
Target detection, Hyperspectral, Endmember extraction,
Multiple instance learning, Hybrid detector, Target characterization
BibRef
Meerdink, S.[Susan],
Bocinsky, J.[James],
Zare, A.[Alina],
Kroeger, N.[Nicholas],
McCurley, C.[Connor],
Shats, D.[Daniel],
Gader, P.[Paul],
Multitarget Multiple-Instance Learning for Hyperspectral Target
Detection,
GeoRS(60), 2022, pp. 1-14.
IEEE DOI
2112
Hyperspectral imaging, Object detection, Training, Training data,
Dictionaries, Libraries, Global Positioning System,
target detection
BibRef
Ozkan, S.,
Kaya, B.,
Akar, G.B.,
EndNet: Sparse AutoEncoder Network for Endmember Extraction and
Hyperspectral Unmixing,
GeoRS(57), No. 1, January 2019, pp. 482-496.
IEEE DOI
1901
Hyperspectral imaging, Neural networks, Standards, Decoding,
Microscopy, Spatial resolution, Endmember extraction,
sparse autoencoder
BibRef
Ozkan, S.,
Akar, G.B.,
Deep Spectral Convolution Network for Hyperspectral Unmixing,
ICIP18(3313-3317)
IEEE DOI
1809
Convolution, Hyperspectral imaging,
Root mean square, Data mining, Probabilistic logic,
Deep Spectral Convolution Networks
BibRef
Gan, Y.Q.[Yu-Quan],
Hu, B.L.[Bing-Liang],
Liu, W.H.[Wei-Hua],
Wang, S.[Shuang],
Zhang, G.[Geng],
Feng, X.P.[Xiang-Peng],
Wen, D.S.[De-Sheng],
Endmember extraction from hyperspectral imagery based on QR
factorisation using givens rotations,
IET-IPR(13), No. 2, February 2019, pp. 332-343.
DOI Link
1902
BibRef
Drumetz, L.,
Meyer, T.R.,
Chanussot, J.,
Bertozzi, A.L.,
Jutten, C.,
Hyperspectral Image Unmixing With Endmember Bundles and Group
Sparsity Inducing Mixed Norms,
IP(28), No. 7, July 2019, pp. 3435-3450.
IEEE DOI
1906
geophysical image processing, hyperspectral imaging,
least squares approximations, optimisation, regression analysis,
convex optimization
BibRef
Xu, M.,
Du, B.,
Fan, Y.,
Endmember Extraction From Highly Mixed Data Using Linear Mixture
Model Constrained Particle Swarm Optimization,
GeoRS(57), No. 8, August 2019, pp. 5502-5511.
IEEE DOI
1908
convex programming, hyperspectral imaging, image processing,
matrix decomposition, particle swarm optimisation,
particle swarm optimization (PSO)
BibRef
Du, B.,
Wei, Q.,
Liu, R.,
An Improved Quantum-Behaved Particle Swarm Optimization for Endmember
Extraction,
GeoRS(57), No. 8, August 2019, pp. 6003-6017.
IEEE DOI
1908
geophysical image processing, hyperspectral imaging,
particle swarm optimisation, remote sensing,
spectral umixing
BibRef
Tong, L.,
Du, B.,
Liu, R.,
Zhang, L.,
An Improved Multiobjective Discrete Particle Swarm Optimization for
Hyperspectral Endmember Extraction,
GeoRS(57), No. 10, October 2019, pp. 7872-7882.
IEEE DOI
1910
evolutionary computation, feature extraction,
hyperspectral imaging, Pareto optimisation,
multiobjective optimization
BibRef
Shen, X.F.[Xiang-Fei],
Bao, W.X.[Wen-Xing],
Hyperspectral Endmember Extraction Using Spatially Weighted Simplex
Strategy,
RS(11), No. 18, 2019, pp. xx-yy.
DOI Link
1909
BibRef
Kowkabi, F.[Fatemeh],
Keshavarz, A.[Ahmad],
Using spectral Geodesic and spatial Euclidean weights of
neighbourhood pixels for hyperspectral Endmember Extraction
preprocessing,
PandRS(158), 2019, pp. 201-218.
Elsevier DOI
1912
Endmember Extraction (EE),
Geodesic and Euclidean distances-based preprocessing (GEPP),
Unmixing
BibRef
Bekit, A.[Adam],
Chang, C.I.[Chein-I],
Lampe, B.[Bernard],
Della Porta, C.J.[Charles J.],
Wu, C.,
N-FINDER for Finding Endmembers in Compressively Sensed Band Domain,
GeoRS(58), No. 2, February 2020, pp. 1087-1101.
IEEE DOI
2001
Sensors, Hyperspectral imaging, Image coding, Compressed sensing,
Matrix decomposition, Sparse matrices,
successive N-FINDR (SC N-FINDR)
BibRef
Lampe, B.[Bernard],
Chang, C.I.[Chein-I],
Bekit, A.[Adam],
Della Porta, C.J.[Charles J.],
Restricted Entropy and Spectrum Properties for the Compressively
Sensed Domain in Hyperspectral Imaging,
GeoRS(58), No. 8, August 2020, pp. 5642-5652.
IEEE DOI
2007
Entropy, Hyperspectral imaging, Sensors, Sparse matrices,
Probabilistic logic, Compressed sensing,
restricted spectrum property (RSP)
BibRef
Della Porta, C.J.,
Chang, C.I.,
Progressive Compressively Sensed Band Processing for Hyperspectral
Classification,
GeoRS(59), No. 3, March 2021, pp. 2378-2390.
IEEE DOI
2103
Image coding, Hyperspectral imaging, Sensors, Measurement, Training,
Compressed sensing,
progressive compressively sensed band classification (PCSBC)
BibRef
Zhu, X.,
Kang, Y.,
Liu, J.,
Estimation of the Number of Endmembers via Thresholding Ridge Ratio
Criterion,
GeoRS(58), No. 1, January 2020, pp. 637-649.
IEEE DOI
2001
Estimation, Hyperspectral imaging,
Eigenvalues and eigenfunctions, Hybrid fiber coaxial cables,
thresholding
BibRef
Jiang, T.X.[Ting-Xuan],
van der Werff, H.[Harald],
van der Meer, F.[Freek],
Classification Endmember Selection with Multi-Temporal Hyperspectral
Data,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link
2006
BibRef
Jiang, X.,
Gong, M.,
Zhan, T.,
Zhang, M.,
Multiobjective Endmember Extraction Based on Bilinear Mixture Model,
GeoRS(58), No. 11, November 2020, pp. 8192-8210.
IEEE DOI
2011
Libraries, Scattering, Mixture models, Hyperspectral imaging,
Indexes, Spatial resolution, Bilinear mixture model (Bi-LMM),
virtual endmember
BibRef
Prades, J.[José],
Safont, G.[Gonzalo],
Salazar, A.[Addisson],
Vergara, L.[Luis],
Estimation of the Number of Endmembers in Hyperspectral Images Using
Agglomerative Clustering,
RS(12), No. 21, 2020, pp. xx-yy.
DOI Link
2011
BibRef
Tao, X.,
Cui, T.,
Plaza, A.,
Ren, P.,
Simultaneously Counting and Extracting Endmembers in a Hyperspectral
Image Based on Divergent Subsets,
GeoRS(58), No. 12, December 2020, pp. 8952-8966.
IEEE DOI
2012
Hyperspectral imaging, Estimation, Optimization,
Eigenvalues and eigenfunctions, Bridges, Indexes, spectral unmixing
BibRef
Tao, X.W.[Xuan-Wen],
Paoletti, M.E.[Mercedes E.],
Haut, J.M.[Juan M.],
Ren, P.[Peng],
Plaza, J.[Javier],
Plaza, A.[Antonio],
Endmember Estimation with Maximum Distance Analysis,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Song, X.,
Zou, L.,
Wu, L.,
Detection of Subpixel Targets on Hyperspectral Remote Sensing Imagery
Based on Background Endmember Extraction,
GeoRS(59), No. 3, March 2021, pp. 2365-2377.
IEEE DOI
2103
Dictionaries, Object detection, Hyperspectral imaging, Data models,
Feature extraction, Machine learning,
target detection
BibRef
Tong, L.,
Du, B.,
Liu, R.,
Zhang, L.,
Tan, K.C.,
Hyperspectral Endmember Extraction by (mu + lambda) Multiobjective
Differential Evolution Algorithm Based on Ranking Multiple Mutations,
GeoRS(59), No. 3, March 2021, pp. 2352-2364.
IEEE DOI
2103
Optimization, Sociology, Statistics, Indexes, Hyperspectral imaging,
Sorting, Endmember extraction (EE)
BibRef
Liu, R.[Rong],
Zhu, X.X.[Xiao-Xiang],
Endmember Bundle Extraction Based on Multiobjective Optimization,
GeoRS(59), No. 10, October 2021, pp. 8630-8645.
IEEE DOI
2109
Optimization, Hyperspectral imaging, Indexes, Data mining,
Particle swarm optimization, Linear programming,
spectral variability
BibRef
Ye, C.L.[Chuan-Long],
Liu, S.W.[Shan-Wei],
Xu, M.M.[Ming-Ming],
Du, B.[Bo],
Wan, J.H.[Jian-Hua],
Sheng, H.[Hui],
An Endmember Bundle Extraction Method Based on Multiscale Sampling to
Address Spectral Variability for Hyperspectral Unmixing,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Wang, Z.[Zhao],
Li, J.Z.[Jian-Zhao],
Liu, Y.T.[Yi-Ting],
Xie, F.[Fei],
Li, P.[Peng],
An Adaptive Surrogate-Assisted Endmember Extraction Framework Based
on Intelligent Optimization Algorithms for Hyperspectral Remote
Sensing Images,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Song, M.P.[Mei-Ping],
Li, Y.[Ying],
Yang, T.T.[Ting-Ting],
Xu, D.Y.[Da-Yong],
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Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Hyperspectral Data, Dimensionality Reduction .