14.2.2.3 Hyperspectral Data, Endmember Extraction

Chapter Contents (Back)
Hyperspectral. Endmember Extraction. See also Number of Features, Dimensionality Reduction.

Rashed, T.[Tarek], Weeks, J.R.[John R.], Roberts, D.A.[Dar A.], Rogan, J.[John], Powell, R.[Rebecca],
Measuring the Physical Composition of Urban Morphology Using Multiple Endmember Spectral Mixture Models,
PhEngRS(69), No. 9, September 2003, pp. 1011-1020.
WWW Link. 0309
The results showed that a majority of the image could be modeled successfully with two- or three-endmember models. BibRef

Yang, F.[Fan], Matsushita, B.[Bunkei], Fukushima, T.[Takehiko],
A pre-screened and normalized multiple endmember spectral mixture analysis for mapping impervious surface area in Lake Kasumigaura Basin, Japan,
PandRS(65), No. 5, September 2010, pp. 479-490.
Elsevier DOI 1003
Impervious surface area; Spectral mixture analysis; Endmember selection; Lake Kasumigaura Basin BibRef

Thompson, D.R., Mandrake, L., Gilmore, M.S., Castano, R.,
Superpixel Endmember Detection,
GeoRS(48), No. 11, November 2010, pp. 4023-4033.
IEEE DOI 1011
BibRef

Plaza, J.[Javier], Hendrix, E.M.T.[Eligius M.T.], García, I.[Inmaculada], Martín, G.[Gabriel], Plaza, A.[Antonio],
On Endmember Identification in Hyperspectral Images Without Pure Pixels: A Comparison of Algorithms,
JMIV(42), No. 2-3, February 2012, pp. 163-175.
WWW Link. 1202
BibRef

Plaza, A.[Antonio], Plaza, J.[Javier], Martin, G.[Gabriel],
Spatial-spectral endmember extraction from hyperspectral imagery using multi-band morphology and volume optimization,
ICIP09(3721-3724).
IEEE DOI 0911
BibRef

Plaza, A., Chang, C.I.,
Impact of Initialization on Design of Endmember Extraction Algorithms,
GeoRS(44), No. 11, November 2006, pp. 3397-3407.
IEEE DOI 0611
BibRef

Wang, J., Chang, C.I.[Chein-I],
Applications of Independent Component Analysis in Endmember Extraction and Abundance Quantification for Hyperspectral Imagery,
GeoRS(44), No. 9, September 2006, pp. 2601-2616.
IEEE DOI 0609
See also Independent Component Analysis-Based Dimensionality Reduction With Applications in Hyperspectral Image Analysis. BibRef

Chang, C.I.[Chein-I], Wu, C.C., Lo, C.S., Chang, M.L.,
Real-Time Simplex Growing Algorithms for Hyperspectral Endmember Extraction,
GeoRS(48), No. 4, April 2010, pp. 1834-1850.
IEEE DOI 1003
BibRef

Chang, C.I.[Chein-I], Xiong, W., Wu, C.C.,
Field-Programmable Gate Array Design of Implementing Simplex Growing Algorithm for Hyperspectral Endmember Extraction,
GeoRS(51), No. 3, March 2013, pp. 1693-1700.
IEEE DOI 1303
BibRef

Chang, I.C.[I C.], Wu, C.C., Tsai, C.T.,
Random N-Finder (N-FINDR) Endmember Extraction Algorithms for Hyperspectral Imagery,
IP(20), No. 3, March 2011, pp. 641-656.
IEEE DOI 1103
BibRef

Zhang, B.[Bing], Sun, X.[Xun], Gao, L.[Lianru], Yang, L.,
Endmember Extraction of Hyperspectral Remote Sensing Images Based on the Ant Colony Optimization (ACO) Algorithm,
GeoRS(49), No. 7, July 2011, pp. 2635-2646.
IEEE DOI 1107
BibRef

Sun, X.[Xu], Yang, L.[Lina], Zhang, B.[Bing], Gao, L.[Lianru], Gao, J.W.[Jian-Wei],
An Endmember Extraction Method Based on Artificial Bee Colony Algorithms for Hyperspectral Remote Sensing Images,
RS(7), No. 12, 2015, pp. 15834.
DOI Link 1601
BibRef

Zhang, B.[Bing], Sun, X.[Xun], Gao, L.[Lianru], Yang, L.,
Endmember Extraction of Hyperspectral Remote Sensing Images Based on the Discrete Particle Swarm Optimization Algorithm,
GeoRS(49), No. 11, November 2011, pp. 4173-4176.
IEEE DOI 1112
BibRef

Mei, S.H.[Shao-Hui], He, M.Y.[Ming-Yi], Zhang, Y.F.[Yi-Fan], Wang, Z.Y.[Zhi-Yong], Feng, D.[Dagan],
Improving Spatial-Spectral Endmember Extraction in the Presence of Anomalous Ground Objects,
GeoRS(49), No. 11, November 2011, pp. 4210-4222.
IEEE DOI 1112
BibRef

Li, H.L.[Hua-Li], Zhang, L.P.[Liang-Pei],
A Hybrid Automatic Endmember Extraction Algorithm Based on a Local Window,
GeoRS(49), No. 11, November 2011, pp. 4223-4238.
IEEE DOI 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 Extraction,
GeoRS(49), No. 11, November 2011, pp. 4177-4193.
IEEE DOI 1112
BibRef

Chan, T.H., Ambikapathi, A., Ma, W.K., Chi, C.Y.,
Robust Affine Set Fitting and Fast Simplex Volume Max-Min for Hyperspectral Endmember Extraction,
GeoRS(51), No. 7, 2013, pp. 3982-3997.
IEEE DOI Data mining; ;Noise; Robustness; Alternating optimization; robust dimension reduction; simplex volume max-min; successive optimization 1307
BibRef

Liu, J.M.[Jun-Min], Zhang, J.S.[Jiang-She],
A New Maximum Simplex Volume Method Based on Householder Transformation for Endmember Extraction,
GeoRS(50), No. 1, January 2012, pp. 104-118.
IEEE DOI 1201
BibRef

Geng, X.R.[Xiu-Rui], Xiao, Z.Q.[Zheng-Qing], Ji, L.[Luyan], 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], Ji, L.[Luyan], Sun, K.[Kang],
Clever eye algorithm for target detection of remote sensing imagery,
PandRS(114), No. 1, 2016, pp. 32-39.
Elsevier DOI 1604
Hyperspectral data BibRef

Graña, M.[Manuel], Veganzones, M.A.[Miguel A.],
An endmember-based distance for content based hyperspectral image retrieval,
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.[Anbing], Xie, Y.[Yichun],
Chaos Theory-Based Data-Mining Technique for Image Endmember Extraction: Laypunov Index and Correlation Dimension (L and D),
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

Xu, Y.L.[Yuan-Liu], Shi, J.C.[Jian-Cheng], Du, J.Y.[Jin-Yang],
An Improved Endmember Selection Method Based on Vector Length for MODIS Reflectance Channels,
RS(7), No. 5, 2015, pp. 6280-6295.
DOI Link 1506
BibRef

Jiao, C., Zare, A.,
Functions of Multiple Instances for Learning Target Signatures,
GeoRS(53), No. 8, August 2015, pp. 4670-4686.
IEEE DOI 1506
Approximation algorithms BibRef

Jiao, C., Zare, A.,
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

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.[Chengye], 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, Hidden Markov model, 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

Sun, W.W.[Wei-Wei], Zhang, D.[Dianfa], Xu, Y.[Yan], Tian, L.[Long], Yang, G.[Gang], Li, W.[Weiyue],
A Probabilistic Weighted Archetypal Analysis Method with Earth Mover's Distance for Endmember Extraction from Hyperspectral Imagery,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link 1708
BibRef


Qian, B., Zhou, J., Tong, L., Shen, X., Liu, F.,
Nonnegative matrix factorization with endmember sparse graph learning for hyperspectral unmixing,
ICIP16(1843-1847)
IEEE DOI 1610
Estimation BibRef

Torres-Madronero, M.C., Velez-Reyes, M.,
Hyperspectral endmember class extraction using clustering and validity indexes,
Southwest16(81-84)
IEEE DOI 1605
Clustering algorithms BibRef

Zhou, Q.L.[Qian-Lan], Zhang, J.[Jing], Tian, Q.[Qi], Zhuo, L.[Li], Geng, W.H.[Wen-Hao],
Automatic Endmember Extraction Using Pixel Purity Index for Hyperspectral Imagery,
MMMod16(II: 207-217).
Springer DOI 1601
BibRef

Zare, A.[Alina], Bchir, O.[Ouiem], Frigui, H.[Hichem], Gader, P.D.[Paul D.],
Hyperspectral image analysis with piece-wise convex endmember estimation and spectral unmixing,
ICIP12(2681-2684).
IEEE DOI 1302
BibRef

Pargal, S.[Sourabh], Agarwal, S.[Shefali], Gupta, P.K.[Prasun Kumar], van der Werff, H.M.A.,
Spatial-spectral endmember extraction for spaceborne hyperspectral data,
ICIIP11(1-6).
IEEE DOI 1112
BibRef

Xu, H., Tian, B., Liu, F.,
An endmember extraction algorithm for hyperspectral images using watershed and normalized cuts,
HighRes11(xx-yy).
PDF File. 1106
BibRef

Luo, B.[Bin], Chanussot, J.[Jocelyn], Doute, S.[Sylvain],
Unsupervised endmember extraction: Application to hyperspectral images from Mars,
ICIP09(2869-2872).
IEEE DOI 0911
BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Hyperspectral Data, Dimensionality Reduction, Band Selection .


Last update:Sep 18, 2017 at 11:34:11