14.2.8.2 Mixed Pixels, Unmixing

Chapter Contents (Back)
Mixed Pixels. 1102
Unmixing. See also Hyperspectral Unmixing.

Kwan, C., Ayhan, B., Chen, G., Wang, J., Ji, B., Chang, C.I.,
A Novel Approach for Spectral Unmixing, Classification, and Concentration Estimation of Chemical and Biological Agents,
GeoRS(44), No. 2, February 2006, pp. 409-419.
IEEE DOI 0602
BibRef

Rogge, D.M., Rivard, B., Zhang, J., Feng, J.,
Iterative Spectral Unmixing for Optimizing Per-Pixel Endmember Sets,
GeoRS(44), No. 12, December 2006, pp. 3725-3736.
IEEE DOI 0701
BibRef

Foody, G.M.[Giles M.], Doan, H.T.X.,
Variability in Soft Classification Prediction and Its Implications for Sub-pixel Scale Change Detection and Super Resolution Mapping,
PhEngRS(73), No. 8, August 2007, pp. 923-934.
WWW Link. 0709
The impacts of class spectral variability on unmixing the the implications for analyses based on soft classification outputs. BibRef

Silvan-Cardenas, J.L., Wang, L.,
Fully Constrained Linear Spectral Unmixing: Analytic Solution Using Fuzzy Sets,
GeoRS(48), No. 11, November 2010, pp. 3992-4002.
IEEE DOI 1011
BibRef

Omachi, M.[Masako], Omachi, S.[Shinichiro],
Pattern Recognition with Gaussian Mixture Models of Marginal Distributions,
IEICE(E94-D), No. 2, February 2011, pp. 317-324.
WWW Link. 1102
BibRef

Yang, Z.Y.[Zu-Yuan], Zhou, G.X.[Guo-Xu], Xie, S.L.[Sheng-Li], Ding, S.X.[Shu-Xue], Yang, J.M.[Jun-Mei], Zhang, J.[Jun],
Blind Spectral Unmixing Based on Sparse Nonnegative Matrix Factorization,
IP(20), No. 4, April 2011, pp. 1112-1125.
IEEE DOI 1103
BibRef

Pu, H.[Hanye], Xia, W.[Wei], Wang, B.[Bin], Jiang, G.M.[Geng-Ming],
A Fully Constrained Linear Spectral Unmixing Algorithm Based on Distance Geometry,
GeoRS(52), No. 2, February 2014, pp. 1157-1176.
IEEE DOI 1402
Monte Carlo methods BibRef

Chen, X.H.[Xue-Hong], Chen, J.[Jin], Jia, X.P.[Xiu-Ping], Somers, B., Wu, J.[Jin], Coppin, P.,
A Quantitative Analysis of Virtual Endmembers' Increased Impact on the Collinearity Effect in Spectral Unmixing,
GeoRS(49), No. 8, August 2011, pp. 2945-2956.
IEEE DOI 1108
BibRef

Li, H.[Hui], Wang, Y.P.[Yun-Peng], Li, Y.[Yan], Wang, X.F.[Xing-Fang],
Pixel-Unmixing Moderate-Resolution Remote Sensing Imagery Using Pairwise Coupling Support Vector Machines: A Case Study,
GeoRS(49), No. 11, November 2011, pp. 4298-4307.
IEEE DOI 1112
BibRef

Boardman, J.W., Kruse, F.A.,
Analysis of Imaging Spectrometer Data Using N-Dimensional Geometry and a Mixture-Tuned Matched Filtering Approach,
GeoRS(49), No. 11, November 2011, pp. 4138-4152.
IEEE DOI 1112
partial linear unmixing. BibRef

Lindblad, J.[Joakim], Sladoje, N.[Nataša],
Coverage segmentation based on linear unmixing and minimization of perimeter and boundary thickness,
PRL(33), No. 6, 15 April 2012, pp. 728-738.
Elsevier DOI 1203
Linear unmixing; Soft classification; Fuzzy segmentation; Pixel coverage model; Energy minimization; Spatial constraints BibRef

Karoui, M.S.[Moussa Sofiane], Deville, Y.[Yannick], Hosseini, S.[Shahram], Ouamri, A.[Abdelaziz],
Blind spatial unmixing of multispectral images: New methods combining sparse component analysis, clustering and non-negativity constraints,
PR(45), No. 12, December 2012, pp. 4263-4278.
Elsevier DOI 1208
Multispectral spatial unmixing; Blind source separation; Sparse component analysis; Correlation; Clustering; Non-negativity constraints BibRef

Warren, R.E., Osher, S.J., Vanderbeek, R.G.,
Multiple Aerosol Unmixing by the Split Bregman Algorithm,
GeoRS(50), No. 9, September 2012, pp. 3271-3279.
IEEE DOI 1209
Not really mixed pixels, but close. BibRef

Zare, A., Gader, P.D., Bchir, O., Frigui, H.,
Piecewise Convex Multiple-Model Endmember Detection and Spectral Unmixing,
GeoRS(51), No. 5, May 2013, pp. 2853-2862.
IEEE DOI 1305
BibRef

Liu, J., Zhang, J.,
Spectral Unmixing via Compressive Sensing,
GeoRS(52), No. 11, November 2014, pp. 7099-7110.
IEEE DOI 1407
Algorithm design and analysis BibRef

Luo, W.[Wenfei], Gao, L.[Lianru], Zhang, R.[Ruihao], Marinoni, A.[Andrea], Zhang, B.[Bing],
Bilinear normal mixing model for spectral unmixing,
IET-IPR(13), No. 2, February 2019, pp. 344-354.
DOI Link 1902
BibRef

Akhtar, N.[Naveed], Shafait, F.[Faisal], Mian, A.[Ajmal],
Efficient classification with sparsity augmented collaborative representation,
PR(65), No. 1, 2017, pp. 136-145.
Elsevier DOI 1702
Multi-class classification BibRef

Li, X., Jia, X., Wang, L., Zhao, K.,
On Spectral Unmixing Resolution Using Extended Support Vector Machines,
GeoRS(53), No. 9, September 2015, pp. 4985-4996.
IEEE DOI 1506
Analytical models BibRef

Kuo, C.Y.[Chun-Yen], Lin, G.X.[Gang-Xuan], Lu, C.S.[Chun-Shien],
A Necessary and Sufficient Condition for Generalized Demixing,
SPLetters(22), No. 11, November 2015, pp. 2049-2053.
IEEE DOI 1509
compressed sensing BibRef

Doxani, G.[Georgia], Mitraka, Z.[Zina], Gascon, F.[Ferran], Goryl, P.[Philippe], Bojkov, B.R.[Bojan R.],
A Spectral Unmixing Model for the Integration of Multi-Sensor Imagery: A Tool to Generate Consistent Time Series Data,
RS(7), No. 10, 2015, pp. 14000.
DOI Link 1511
BibRef

Uezato, T., Murphy, R.J., Melkumyan, A., Chlingaryan, A.,
A Novel Spectral Unmixing Method Incorporating Spectral Variability Within Endmember Classes,
GeoRS(54), No. 5, May 2016, pp. 2812-2831.
IEEE DOI 1604
Gaussian processes BibRef

Uezato, T., Murphy, R.J., Melkumyan, A., Chlingaryan, A.,
A Novel Endmember Bundle Extraction and Clustering Approach for Capturing Spectral Variability Within Endmember Classes,
GeoRS(54), No. 11, November 2016, pp. 6712-6731.
IEEE DOI 1610
Data mining BibRef

Uezato, T., Murphy, R.J., Melkumyan, A., Chlingaryan, A.,
Incorporating Spatial Information and Endmember Variability Into Unmixing Analyses to Improve Abundance Estimates,
IP(25), No. 12, December 2016, pp. 5563-5575.
IEEE DOI 1612
Gaussian processes BibRef

Xu, C.[Chao], Liu, Z.L.[Zhao-Li], Hou, G.L.[Guang-Lei],
Simulation of the Impact of a Sensor's PSF on Mixed Pixel Decomposition: 1. Nonuniformity Effect,
RS(8), No. 5, 2016, pp. 437.
DOI Link 1606
BibRef

Pan, Z.W., Shen, H.L., Li, C., Chen, S.J., Xin, J.H.,
Fast Multispectral Imaging by Spatial Pixel-Binning and Spectral Unmixing,
IP(25), No. 8, August 2016, pp. 3612-3625.
IEEE DOI 1608
image reconstruction BibRef

Chen, F., Wang, K., Tang, T.F.,
Spectral Unmixing Using a Sparse Multiple-Endmember Spectral Mixture Model,
GeoRS(54), No. 10, October 2016, pp. 5846-5861.
IEEE DOI 1610
geophysical image processing BibRef

Qi, K.L.[Kun-Lun], Liu, W.X.[Wen-Xuan], Yang, C.[Chao], Guan, Q.F.[Qing-Feng], Wu, H.Y.[Hua-Yi],
Multi-Task Joint Sparse and Low-Rank Representation for the Scene Classification of High-Resolution Remote Sensing Image,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702
BibRef

Qi, K.L.[Kun-Lun], Yang, C.[Chao], Guan, Q.F.[Qing-Feng], Wu, H.Y.[Hua-Yi], Gong, J.Y.[Jian-Ya],
A Multiscale Deeply Described Correlatons-Based Model for Land-Use Scene Classification,
RS(9), No. 9, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Williams, M.D.[McKay D.], Parody, R.J.[Robert J.], Fafard, A.J.[Alexander J.], Kerekes, J.P.[John P.], van Aardt, J.[Jan],
Validation of Abundance Map Reference Data for Spectral Unmixing,
RS(9), No. 5, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Williams, M.D.[McKay D.], Kerekes, J.P.[John P.], van Aardt, J.[Jan],
Application of Abundance Map Reference Data for Spectral Unmixing,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Berman, M., Bischof, L., Lagerstrom, R., Guo, Y., Huntington, J., Mason, P., Green, A.A.,
A Comparison Between Three Sparse Unmixing Algorithms Using a Large Library of Shortwave Infrared Mineral Spectra,
GeoRS(55), No. 6, June 2017, pp. 3588-3610.
IEEE DOI 1706
Absorption, Algorithm design and analysis, Australia, Frequency selective surfaces, Geologic measurements, Libraries, Minerals, Canonical variates (CVs), cubic spline, linear unmixing, shortwave infrared (SWIR) spectra, sparse unmixing, spectral, library BibRef

Ahmed, A.M.[Asmau M.], Duran, O.[Olga], Zweiri, Y.[Yahya], Smith, M.[Mike],
Hybrid Spectral Unmixing: Using Artificial Neural Networks for Linear/Non-Linear Switching,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Ma, J.H.[Jian-Hang], Zhang, W.J.[Wen-Juan], Marinoni, A.[Andrea], Gao, L.[Lianru], Zhang, B.[Bing],
An Improved Spatial and Temporal Reflectance Unmixing Model to Synthesize Time Series of Landsat-Like Images,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810
BibRef

Huang, R.S.[Ri-Sheng], Li, X.R.[Xiao-Run], Lu, H.Q.[Hai-Qiang], Li, J.[Jing], Zhao, L.Y.[Liao-Ying],
Parameterized Nonlinear Least Squares for Unsupervised Nonlinear Spectral Unmixing,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link 1902
BibRef

Li, Z.[Zeng], Chen, J.[Jie], Rahardja, S.[Susanto],
Kernel-Based Nonlinear Spectral Unmixing with Dictionary Pruning,
RS(11), No. 5, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Granero-Belinchon, C.[Carlos], Michel, A.[Aurelie], Lagouarde, J.P.[Jean-Pierre], Sobrino, J.A.[Jose A.], Briottet, X.[Xavier],
Multi-Resolution Study of Thermal Unmixing Techniques over Madrid Urban Area: Case Study of TRISHNA Mission,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Deng, Y.B.[Ying-Bin], Chen, R.R.[Ren-Rong], Wu, C.S.[Chang-Shan],
Examining the Deep Belief Network for Subpixel Unmixing with Medium Spatial Resolution Multispectral Imagery in Urban Environments,
RS(11), No. 13, 2019, pp. xx-yy.
DOI Link 1907
BibRef


Baghbaderani, R.K., Qi, H.,
Incorporating Spectral Unmixing in Satellite Imagery Semantic Segmentation,
ICIP19(2449-2453)
IEEE DOI 1910
Satellite image, semantic segmentation, deep learning, spectral unmixing BibRef

Ke, J., Guo, Y., Sowmya, A.,
A Fast Approximate Spectral Unmixing Algorithm Based on Segmentation,
PBVS17(260-266)
IEEE DOI 1709
Algorithm design and analysis, Approximation algorithms, Classification algorithms, Computational modeling, Estimation, Image segmentation, Libraries BibRef

Neumayer, S.[Sebastian], Nimmer, M.[Max], Steidl, G.[Gabriele], Stephani, H.[Henrike],
On a Projected Weiszfeld Algorithm,
SSVM17(486-497).
Springer DOI 1706
Spectral demixing. BibRef

Figliuzzi, B.[Bruno], Velasco-Forero, S.[Santiago], Bilodeau, M.[Michel], Angulo, J.[Jesus],
A Bayesian Approach to Linear Unmixing in the Presence of Highly Mixed Spectra,
ACIVS16(263-274).
Springer DOI 1611
BibRef

Ziemann, A.K.,
Local spectral unmixing for target detection,
Southwest16(77-80)
IEEE DOI 1605
Clutter BibRef

Pang, Q.Y.[Qing-Yu], Yu, J.[Jing], Sun, W.D.[Wei-Dong],
A spectral unmixing method based on wavelet weighted similarity,
ICIP15(1865-1869)
IEEE DOI 1512
nonnegative matrix factorization BibRef

Ramak, R., Valadan Zouj, M.J., Mojaradi, B.,
Improving Linear Spectral Unmixing Through Local Endmember Detection,
PIA15(177-181).
DOI Link 1504
BibRef

Legendre, M.[Maxime], Moussaoui, S.[Said], Chouzenoux, E.[Emilie], Idier, J.[Jerome],
Primal-dual interior-point optimization based on majorization-minimization for edge-preserving spectral unmixing,
ICIP14(4161-4165)
IEEE DOI 1502
Approximation algorithms BibRef

Jenzri, H.[Hamdi], Frigui, H.[Hichem], Gader, P.[Paul],
Robust Context Dependent Spectral Unmixing,
ICPR14(643-647)
IEEE DOI 1412
Clustering algorithms BibRef

Wemmert, C.[Cedric], Kruger, J.M.[Juliane M.], Forestier, G.[Germain], Sternberger, L.[Ludovic], Feuerhake, F.[Friedrich], Gancarski, P.[Pierre],
Stain unmixing in brightfield multiplexed immunohistochemistry,
ICIP13(1125-1129)
IEEE DOI 1402
Deconvolution BibRef

Xi, L., Xiaoling, C.,
Spatial Interpolation As A Tool For Spectral Unmixing Of Remotely Sensed Images,
ISPRS12(XXXIX-B7:209-212).
DOI Link 1209
BibRef

Michishita, R., Jiang, Z., Xu, B.,
Spectral Unmixing Of Blended Reflectance For Denser Time-series Mapping Of Wetlands,
ISPRS12(XXXIX-B8:491-496).
DOI Link 1209
BibRef

Howard, A.M., Bernardes, S., Nibbelink, N., Biondi, L., Presotto, A., Fragaszy, D.M., Madden, M.,
A Maximum Entropy Model Of The Bearded Capuchin Monkey Habitat Incorporating Topography And Spectral Unmixing Analysis,
AnnalsPRS(I-2), No. 2012, pp. 7-11.
HTML Version. 1209
BibRef

Alterman, M., Schechner, Y.Y., Weiss, A.,
Multiplexed fluorescence unmixing,
ICCP10(1-8).
IEEE DOI 1208
BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Mixed Pixels, Subpixel Classification .


Last update:Jun 29, 2020 at 10:24:28