14.2.2.1 High Dimensional Data, Hyperspectral Data, Hyper-Spectral Data Classification

Bryant, J.[Jack],
On the clustering of multidimensional pictorial data,
PR(11), No. 2, 1979, pp. 115-125.
WWW Version. 0309
BibRef

Eden, G., Gelsema, E.S.,
Investigation of multidimensional data using the interactive pattern analysis system ISPAHAN,
PR(11), No. 5-6, 1979, pp. 391-399.
WWW Version. 0309
BibRef

Gelsema, E.S., Eden, G.,
Mapping algorithms in ISPAHAN,
PR(12), No. 3, 1980, pp. 127-136.
WWW Version. 0309
BibRef

Gelsema, E.S., Timmers, T.,
An interactive implementation of nonparametric partitioning in ISPAHAN,
ICPR88(II: 1062-1064).
IEEE DOI Link 8811
BibRef

Curington, I.J.[Ian J.], Cannon, S.E.[Stephen E.],
Multiband image classification with a distributed architecture,
IVC(3), No. 2, May 1985, pp. 80-84.
WWW Version. 0401
BibRef

Chen, C.C.T.[C.C. Thomas], and Landgrebe, D.A.[David A.],
A Spectral Feature Design System for the HIRIS/MODIS Era,
GeoRS(27), No. 6, November 1989, pp. 681-686.
IEEE Top Reference. BibRef 8911

Ismail, M.A.[Mohamed A.], Kamel, M.S.[Mohamed S.],
Multidimensional data clustering utilizing hybrid search strategies,
PR(22), No. 1, 1989, pp. 75-89.
WWW Version. 0309
BibRef

Yousri, N.A.[Noha A.], Kamel, M.S.[Mohamed S.], Ismail, M.A.[Mohamed A.],
A distance-relatedness dynamic model for clustering high dimensional data of arbitrary shapes and densities,
PR(42), No. 7, July 2009, pp. 1193-1209.
Elsevier DOI Link
WWW Version. 0903
BibRef
Earlier:
A novel validity measure for clusters of arbitrary shapes and densities,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef
And:
Finding Arbitrary Shaped Clusters for Character Recognition,
ICIAR08(xx-yy).
Springer DOI Link 0806
Clustering; Dynamic model; Arbitrary shaped clusters; Arbitrary density clusters; High dimensional data; Distance-relatedness BibRef

Zhang, Q.W.[Qi-Wen], Wang, Q.R.[Qen Ring], Boyle, R.D.[Roger D.],
A clustering algorithm for data-sets with a large number of classes,
PR(24), No. 4, 1991, pp. 331-340.
WWW Version. 0401
BibRef

Aeberhard, S.[Stefan], Coomans, D.[Danny], de Vel, O.[Olivier],
Comparative analysis of statistical pattern recognition methods in high dimensional settings,
PR(27), No. 8, August 1994, pp. 1065-1077.
WWW Version. 0401
BibRef

Hoffbeck, J.P., Landgrebe, D.A.,
Classification of Remote Sensing Images Having High Spectral Resolution,
RSE(57), No. 3, September 1996, pp. 119-126. 9609
Hyperspectral. Use the techniques of chemistry spectroscopy for remotely sensed data.
PDF Version. BibRef

Jimenez, L.O.[Luis O.], and Landgrebe, D.A.[David A.],
Supervised Classification in High-Dimensional Space: Geometrical, Statistical, and Asymptotical Properties of Multivariate Data,
SMC-C(28), No. 1, February 1998, pp. 39-54. 9806
Hyperspectral.
PDF Version. BibRef

Jimenez, L.O., Landgrebe, D.A.,
Hyperspectral Data Analysis and Supervised Feature Reduction Via Projection Pursuit,
GeoRS(7), No. 6, November 1999, pp. 2653.
IEEE Top Reference. 9911
BibRef

Haertel, V., Landgrebe, D.A.,
On the Classification of Classes with Nearly Equal Spectral Response in Remote Sensing Hyperspectral Image Data,
GeoRS(37), No. 5, September 1999, pp. 2374.
IEEE Top Reference. BibRef 9909

Jackson, Q., Landgrebe, D.A.,
An adaptive classifier design for high-dimensional data analysis with a limited training data set,
GeoRS(39), No. 12, December 2001, pp. 2664-2679.
IEEE Top Reference. 0201
BibRef

Jackson, Q., Landgrebe, D.A.,
An adaptive method for combined covariance estimation and classification,
GeoRS(40), No. 5, May 2002, pp. 1082-1087.
IEEE Top Reference. 0206
BibRef

Nascimento, S.M.C., Ferreira, F., and Foster, D.H.,
Statistics of spatial cone-excitation ratios in natural scenes,
JOSA-A(19), No. 8, August 2002, pp. 1484-1490.
PDF Version. Dataset, Hyperspectral.
HTML Version. BibRef 0208

Foster, D.H., Nascimento, S.M.C., Amano, K.,
Information limits on neural identification of coloured surfaces in natural scenes,
Visual Neuroscience(21), 2004, pp. 331-336.
PDF Version. Dataset, Hyperspectral.
HTML Version. BibRef 0400

Kim, B., and Landgrebe, D.A.,
Hierarchical Classifier Design in High Dimensional, Numerous Class Cases,
GeoRS(29), No. 4, July 1991, pp. 518-528.
IEEE Top Reference. BibRef 9107

Dundar, M.M., Landgrebe, D.A.,
A model-based mixture-supervised classification approach in hyperspectral data analysis,
GeoRS(40), No. 12, December 2002, pp. 2692-2699.
IEEE Top Reference. 0301
BibRef

Madhok, V., Landgrebe, D.A.,
A process model for remote sensing data analysis,
GeoRS(40), No. 3, March 2002, pp. 680-686.
IEEE Top Reference. 0206
BibRef

Kuo, B.C., Landgrebe, D.A.,
A robust classification procedure based on mixture classifiers and nonparametric weighted feature extraction,
GeoRS(40), No. 11, November 2002, pp. 2486-2494.
IEEE Top Reference. 0301
BibRef

Dundar, M.M., Landgrebe, D.A.,
A Cost-Effective Semisupervised Classifier Approach With Kernels,
GeoRS(42), No. 1, January 2004, pp. 264-270.
IEEE Abstract. IEEE Top Reference. 0402
BibRef

Dundar, M.M., Landgrebe, D.A.,
Toward an Optimal Supervised Classifier for the Analysis of Hyperspectral Data,
GeoRS(42), No. 1, January 2004, pp. 271-277.
IEEE Abstract. IEEE Top Reference. 0402
BibRef

Nene, S.A.[Sameer A.], Nayar, S.K.[Shree K.],
A Simple Algorithm for Nearest-Neighbor Search in High Dimensions,
PAMI(19), No. 9, September 1997, pp. 989-1003.
IEEE Abstract. IEEE Top Reference.
WWW Version. 9710
Find the nearest neighbor only if it is within some distance. Uses projections of the search space. BibRef

Cortijo, F.J., de la Blanca, N.P.[N. Perez],
The performance of regularized discriminant analysis versus non-parametric classifiers applied to high-dimensional image classification,
JRS(20), No. 17, November 1999, pp. 3345. BibRef 9911

Carr, J.R.[James R.], Matanawi, K.[Korblaah],
Correspondence Analysis for Principal Components Transformation of Multispectral and Hyperspectral Digital Images,
PhEngRS(65), No. 8, August 1999, pp. 909. captures 96% of the original image variance in first principal component. BibRef 9908

Benediktsson, J.A., Kanellopoulos, I.,
Classification of Multisource and Hyperspectral Data Based on Decision Fusion,
GeoRS(37), No. 3, May 1999, pp. 1367.
IEEE Top Reference. BibRef 9905

Benediktsson, J.A., Palmason, J.A., Sveinsson, J.R.,
Classification of Hyperspectral Data From Urban Areas Based on Extended Morphological Profiles,
GeoRS(43), No. 3, March 2005, pp. 480-491.
IEEE Abstract. IEEE Top Reference. 0501
See also Multisource remote sensing data classification based on consensus and pruning. BibRef

Fauvel, M., Benediktsson, J.A., Chanussot, J., Sveinsson, J.R.,
Spectral and Spatial Classification of Hyperspectral Data Using SVMs and Morphological Profiles,
GeoRS(46), No. 11, November 2008, pp. 3804-3814.
IEEE DOI Link 0812
BibRef

Tarabalka, Y., Benediktsson, J.A., Chanussot, J.[Jocelyn],
Spectral-Spatial Classification of Hyperspectral Imagery Based on Partitional Clustering Techniques,
GeoRS(47), No. 8, August 2009, pp. 2973-2987.
IEEE DOI Link 0907
BibRef

Fauvel, M.[Mathieu], Chanussot, J.[Jocelyn], Benediktsson, J.A.[Jon Atli],
Adaptive pixel neighborhood definition for the classification of hyperspectral images with support vector machines and composite kernel,
ICIP08(1884-1887).
IEEE DOI Link 0810
BibRef

Jimenez, L.O., Morales-Morell, A., Creus, A.,
Classification of Hyperdimensional Data Based on Feature and Decision Fusion Approaches Using Projection Pursuit, Majority Voting, and Neural Networks,
GeoRS(37), No. 3, May 1999, pp. 1360.
IEEE Top Reference. BibRef 9905

Ifarraguerri, A., Chang, C.I.,
Multispectral and Hyperspectral Image Analysis with Convex Cones,
GeoRS(37), No. 2, March 1999, pp. 756.
IEEE Top Reference. BibRef 9903

Ifarraguerri, A., Chang, C.I.[Chein-I],
Unsupervised Hyperspectral Image Analysis with Projection Pursuit,
GeoRS(38), No. 6, November 2000, pp. 2529-2538.
IEEE Top Reference. 0011
BibRef

Chang, C.I.[Chein-I],
Hyperspectral Imaging: Techniques for Spectral Detection and Classification,
Plenum2004. ISBN:0-306-47483-2.
HTML Version. BibRef 0400

Tu, T.M.[Te-Ming], Shyu, H.C.[Hsuen-Chyun], Lee, C.H.[Ching-Hai], Chang, C.I.[Chein-I],
An oblique subspace projection approach for mixed pixel classification in hyperspectral images,
PR(32), No. 8, August 1999, pp. 1399-1408.
WWW Version. See also Anomaly detection and classification for hyperspectral imagery. BibRef 9908

Pesses, M.E.,
Least-Squares-Filter Vector Hybrid Approach to Hyperspectral Subpixel Demixing,
GeoRS(37), No. 2, March 1999, pp. 846.
IEEE Top Reference. BibRef 9903

McGwire, K.[Kenneth], Minor, T.[Timothy], Fenstermaker, L.[Lynn],
Hyperspectral Mixture Modeling for Quantifying Sparse Vegetation Cover in Arid Environments,
RSE(72), No. 3, 2000, pp. 360-374. 0005
BibRef

Schweizer, S.M., Moura, J.M.F.,
Efficient detection in hyperspectral imagery,
IP(10), No. 4, April 2001, pp. 584-597.
IEEE DOI Link 0104
BibRef

Nielsen, A.A.[Allan Aasbjerg],
Spectral Mixture Analysis: Linear and Semi-parametric Full and Iterated Partial Unmixing in Multi- and Hyperspectral Image Data,
IJCV(42), No. 1-2, April-May 2001, pp. 17-37.
WWW Version. 0106
BibRef
And: JMIV(15), No. 1/2, July 2001, pp. 17-37.
WWW Version. 0106
BibRef

Nielsen, A.A.,
Linear Mixture Models, Full and Partial Unmixing in Multi- and Hyperspectral Image Data,
SCIA99(Remote Sensing). BibRef 9900

Landgrebe, D.A., Serpico, S.B., Crawford, M.M., Singhroy, V.,
Introduction to the special issue on analysis of hyperspectral image data,
GeoRS(39), No. 7, July 2001, pp. 1343-1345.
IEEE Top Reference. 0108
BibRef

Healey, G., Slater, D.A.,
Models and Methods for Automated Material Indentification in Hyperspectral Imagery Acquired under Unknown Illumination and Atmospheric Conditions,
GeoRS(37), No. 6, November 1999, pp. 2707-2717.
IEEE Top Reference. BibRef 9911

Suen, P., Healey, G., Slater, D.A.,
The impact of viewing geometry on material discriminability in hyperspectral images,
GeoRS(39), No. 7, July 2001, pp. 1352-1359.
IEEE Top Reference. 0108
BibRef

Kumar, S., Ghosh, J., Crawford, M.M.,
Best-bases feature extraction algorithms for classification of hyperspectral data,
GeoRS(39), No. 7, July 2001, pp. 1368-1379.
IEEE Top Reference. 0108
Generalized Local Discriminant Bases BibRef

Ham, J., Chen, Y., Crawford, M.M., Ghosh, J.,
Investigation of the Random Forest Framework for Classification of Hyperspectral Data,
GeoRS(43), No. 3, March 2005, pp. 492-501.
IEEE Abstract. IEEE Top Reference. 0501
BibRef

Rajan, S., Ghosh, J., Crawford, M.M.,
Exploiting Class Hierarchies for Knowledge Transfer in Hyperspectral Data,
GeoRS(44), No. 11, November 2006, pp. 3408-3417.
IEEE DOI Link 0611
BibRef

Rajan, S., Ghosh, J., Crawford, M.M.,
An Active Learning Approach to Hyperspectral Data Classification,
GeoRS(46), No. 4, April 2008, pp. 1231-1242.
IEEE DOI Link 0803
BibRef

Funk, C.C., Theiler, J., Roberts, D.A., Borel, C.C.,
Clustering to improve matched filter detection of weak gas plumes in hyperspectral thermal imagery,
GeoRS(39), No. 7, July 2001, pp. 1410-1420.
IEEE Top Reference. 0108
BibRef

Aiazzi, B., Alparone, L., Barducci, A., Baronti, S., Pippi, I.,
Information-theoretic assessment of sampled hyperspectral imagers,
GeoRS(39), No. 7, July 2001, pp. 1447-1458.
IEEE Top Reference. 0108
BibRef

Lewis, M., Jooste, V., de Gasparis, A.A.,
Discrimination of arid vegetation with airborne multispectral scanner hyperspectral imagery,
GeoRS(39), No. 7, July 2001, pp. 1471-1479.
IEEE Top Reference. 0108
BibRef

Garcia, M., Ustin, S.L.,
Detection of interannual vegetation responses to climatic variability using AVIRIS data in a coastal savanna in california,
GeoRS(39), No. 7, July 2001, pp. 1480-1490.
IEEE Top Reference. 0108
BibRef

Tsai, F.[Fuan], Philpot, W.D.,
A derivative-aided hyperspectral image analysis system for land-cover classification,
GeoRS(40), No. 2, February 2002, pp. 416-425.
IEEE Top Reference. 0205
BibRef

Thai, B.[Bea], Healey, G.[Glenn],
Invariant subpixel material detection in hyperspectral imagery,
GeoRS(40), No. 3, March 2002, pp. 599-608.
IEEE Top Reference. 0206
BibRef
And:
Invariant Subpixel Material Identification in Hyperspectral Imagery,
DARPA98(809-814). BibRef
Earlier:
Using a Linear Subspace Approach for Invariant Subpixel Material Identification in Airborne Hyperspectral Imagery,
CVPR99(I: 567-572).
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef

Jia, X.P.[Xiu-Ping], Richards, J.A.,
Cluster-space representation for hyperspectral data classification,
GeoRS(40), No. 3, March 2002, pp. 593-598.
IEEE Top Reference. 0206
BibRef

Jia, X.P.[Xiu-Ping], Richards, J.A.,
Efficient transmission and classification of hyperspectral image data,
GeoRS(41), No. 5, May 2003, pp. 1129-1131.
IEEE Abstract. IEEE Top Reference. 0307
BibRef

Holden, H.[Heather], LeDrew, E.[Ellsworth],
Measuring and modeling water column effects on hyperspectral reflectance in a coral reef environment,
RSE(81), No. 2-3, August 2002, pp. 300-308.
HTML Version. 0206
BibRef

Bakker, W.H., Schmidt, K.S.,
Hyperspectral edge filtering for measuring homogeneity of surface cover types,
PandRS(56), No. 4, July 2002, pp. 246-256.
HTML Version. 0207
BibRef

Priebe, C.E.[Carey E.], Marchette, D.J.[David J.],
Adaptive mixture density estimation,
PR(26), No. 5, May 1993, pp. 771-785.
WWW Version. 0401
BibRef

Priebe, C.E.[Carey E.], Marchette, D.J.[David J.],
Adaptive mixtures: Recursive nonparametric pattern recognition,
PR(24), No. 12, 1991, pp. 1197-1209.
WWW Version. 0401
BibRef

Marchette, D.J.[David J.], Priebe, C.E.[Carey E.],
Characterizing the scale dimension of a high-dimensional classification problem,
PR(36), No. 1, January 2003, pp. 45-60.
WWW Version. 0210
BibRef

Bruce, L.M., Koger, C.H., Li, J.[Jiang],
Dimensionality reduction of hyperspectral data using discrete wavelet transform feature extraction,
GeoRS(40), No. 10, October 2002, pp. 2331-2338.
IEEE Top Reference. 0301
BibRef

Kaewpijit, S., Le Moigne, J., El-Ghazawi, T.,
Automatic reduction of hyperspectral imagery using wavelet spectral analysis,
GeoRS(41), No. 4, April 2003, pp. 863-871.
IEEE Abstract. IEEE Top Reference. 0307
BibRef

Baltsavias, E.P.[Emmanuel P.],
Special section on Image Spectroscopy and Hyperspectral Imaging,
PandRS(57), No. 3, December 2002, pp. 169-170.
WWW Version. 0307
BibRef

Staenz, K., Secker, J., Gao, B.C., Davis, C., Nadeau, C.,
Radiative transfer codes applied to hyperspectral data for the retrieval of surface reflectance,
PandRS(57), No. 3, December 2002, pp. 194-203.
WWW Version. 0307
BibRef

Rahman, A.F.[Abdullah F.], Gamon, J.A.[John A.], Sims, D.A.[Daniel A.], Schmidts, M.[Miriam],
Optimum pixel size for hyperspectral studies of ecosystem function in southern California chaparral and grassland,
RSE(84), No. 2, February 2003, pp. 192-207.
WWW Version. 0309
BibRef

Verhoef, W.[Wout], Bach, H.[Heike],
Simulation of hyperspectral and directional radiance images using coupled biophysical and atmospheric radiative transfer models,
RSE(87), No. 1, 15 September 2003, pp. 23-41.
WWW Version. 0309
BibRef

Guo, D.[Diansheng], Peuquet, D.J.[Donna J.], Gahegan, M.[Mark],
ICEAGE: Interactive Clustering and Exploration of Large and High-Dimensional Geodata,
GeoInfo(7), No. 3, September 2003, pp. 229-253.
WWW Version. 0309
BibRef

Bachmann, C.M.,
Improving the performance of classifiers in high-dimensional remote sensing applications: an adaptive resampling strategy for error-prone exemplars (ARESEPE),
GeoRS(41), No. 9, September 2003, pp. 2101-2112.
IEEE Abstract. IEEE Top Reference. 0310
BibRef

Paclík, P.[Pavel], Duin, R.P.W.[Robert P. W.],
Dissimilarity-based classification of spectra: computational issues,
RealTimeImg(9), No. 4, August 2003, pp. 237-244.
WWW Version.
PDF Version. 0311
BibRef

Plaza, A.[Antonio], Martinez, P.[Pablo], Perez, R.[Rosa], Plaza, J.[Javier],
A new approach to mixed pixel classification of hyperspectral imagery based on extended morphological profiles,
PR(37), No. 6, June 2004, pp. 1097-1116.
WWW Version. 0405
BibRef

Plaza, A.[Antonio], Martinez, P.[Pablo], Plaza, J.[Javier], Perez, R.[Rosa],
Dimensionality Reduction and Classification of Hyperspectral Image Data Using Sequences of Extended Morphological Transformations,
GeoRS(43), No. 3, March 2005, pp. 466-479.
IEEE Abstract. IEEE Top Reference. 0501
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 Link 0611
BibRef

Chang, C.I.[Chein-I], Du, Q.[Qian],
Estimation of number of spectrally distinct signal sources in hyperspectral imagery,
GeoRS(42), No. 3, March 2004, pp. 608-619.
IEEE Abstract. IEEE Top Reference. 0407
BibRef

Chang, C.I., Wang, S.,
Constrained Band Selection for Hyperspectral Imagery,
GeoRS(44), No. 6, June 2006, pp. 1575-1585.
IEEE DOI Link 0606
BibRef

Wang, J., Chang, C.I.,
Independent Component Analysis-Based Dimensionality Reduction With Applications in Hyperspectral Image Analysis,
GeoRS(44), No. 6, June 2006, pp. 1586-1600.
IEEE DOI Link 0606
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 Link 0609
BibRef

Nascimento, J.M.P., Bioucas-Dias, J.M.,
Does Independent Component Analysis Play a Role in Unmixing Hyperspectral Data?,
GeoRS(43), No. 1, January 2005, pp. 175-187.
IEEE Abstract. IEEE Top Reference. 0501
BibRef

Nascimento, J.M.P.[José M. P.], Bioucas-Dias, J.M.B.[José M.B.],
Vertex Component Analysis: A Fast Algorithm to Unmix Hyperspectral Data,
GeoRS(43), No. 4, April 2005, pp. 898-910.
IEEE Abstract. IEEE Top Reference. 0501
BibRef
And:
Dependent Component Analysis: A Hyperspectral Unmixing Algorithm,
IbPRIA07(II: 612-619).
Springer DOI Link 0706
BibRef

Bioucas-Dias, J.M., Nascimento, J.M.P.,
Hyperspectral Subspace Identification,
GeoRS(46), No. 8, August 2008, pp. 2435-2445.
IEEE DOI Link 0808
BibRef

Borges, J.S.[Janete S.], Bioucas-Dias, J.M.B.[José M.B.], Marçal, A.R.S.[André R. S.],
Bayesian Hyperspectral Image Segmentation with Discriminative Class Learning,
IbPRIA07(I: 22-29).
Springer DOI Link 0706
BibRef

Bachmann, C.M., Ainsworth, T.L., Fusina, R.A.,
Exploiting Manifold Geometry in Hyperspectral Imagery,
GeoRS(43), No. 3, March 2005, pp. 441-454.
IEEE Abstract. IEEE Top Reference. 0501
BibRef

Camps-Valls, G., Bruzzone, L.,
Kernel-Based Methods for Hyperspectral Image Classification,
GeoRS(43), No. 6, June 2005, pp. 1351-1362.
IEEE Abstract. IEEE Top Reference. 0506
BibRef

Camps-Valls, G., Bandos Marsheva, T.V., Zhou, D.,
Semi-Supervised Graph-Based Hyperspectral Image Classification,
GeoRS(45), No. 10, October 2007, pp. 3044-3054.
IEEE DOI Link 0711
BibRef

Bandos, T.V., Bruzzone, L., Camps-Valls, G.,
Classification of Hyperspectral Images With Regularized Linear Discriminant Analysis,
GeoRS(47), No. 3, March 2009, pp. 862-873.
IEEE DOI Link 0903
BibRef

Camps-Valls, G., Serrano-López, A.J., Gómez-Chova, L., Martín-Guerrero, J.D., Calpe-Maravilla, J., Moreno, J.,
Regularized RBF Networks for Hyperspectral Data Classification,
ICIAR04(II: 429-436).
WWW Version. 0409
BibRef

Capobianco, L., Garzelli, A., Camps-Valls, G.,
Target Detection With Semisupervised Kernel Orthogonal Subspace Projection,
GeoRS(47), No. 11, November 2009, pp. 3822-3833.
IEEE DOI Link 0911
BibRef

Neher, R., Srivastava, A.,
A Bayesian MRF Framework for Labeling Terrain Using Hyperspectral Imaging,
GeoRS(43), No. 6, June 2005, pp. 1363-1374.
IEEE Abstract. IEEE Top Reference. 0506
BibRef

Moshou, D., Bravo, C., Oberti, R., West, J., Bodria, L., McCartney, A., Ramon, H.,
Plant disease detection based on data fusion of hyper-spectral and multi-spectral fluorescence imaging using Kohonen maps,
RealTimeImg(11), No. 2, April 2005, pp. 75-83.
WWW Version. 0506
BibRef

Tatzer, P.[Petra], Wolf, M.[Markus], Panner, T.[Thomas],
Industrial application for inline material sorting using hyperspectral imaging in the NIR range,
RealTimeImg(11), No. 2, April 2005, pp. 99-107.
WWW Version. 0506
BibRef

Pilevar, A.H., Sukumar, M.,
GCHL: A grid-clustering algorithm for high-dimensional very large spatial data bases,
PRL(26), No. 7, 15 May 2005, pp. 999-1010.
WWW Version. 0506
BibRef

Purkis, S.J.,
A 'Reef-Up' Approach to Classifying Coral Habitats From IKONOS Imagery,
GeoRS(43), No. 6, June 2005, pp. 1375-1390.
IEEE Abstract. IEEE Top Reference. 0506
Using hyperspectral data, calibrate based on field measurements of reflectance. BibRef

Othman, H., Qian, S.E.,
Noise Reduction of Hyperspectral Imagery Using Hybrid Spatial-Spectral Derivative-Domain Wavelet Shrinkage,
GeoRS(44), No. 2, February 2006, pp. 397-408.
IEEE DOI Link 0602
BibRef

Zhong, Y., Zhang, L., Huang, B., Li, P.,
An Unsupervised Artificial Immune Classifier for Multi/Hyperspectral Remote Sensing Imagery,
GeoRS(44), No. 2, February 2006, pp. 420-431.
IEEE DOI Link 0602
BibRef

Zhong, Y., Zhang, L., Gong, J., Li, P.,
A Supervised Artificial Immune Classifier for Remote-Sensing Imagery,
GeoRS(45), No. 12, December 2007, pp. 3957-3966.
IEEE DOI Link 0711
BibRef

Zhang, L., Zhong, Y., Huang, B., Gong, J., Li, P.,
Dimensionality Reduction Based on Clonal Selection for Hyperspectral Imagery,
GeoRS(45), No. 12, December 2007, pp. 4172-4186.
IEEE DOI Link 0711
BibRef

Brown, A.J.,
Spectral Curve Fitting for Automatic Hyperspectral Data Analysis,
GeoRS(44), No. 6, June 2006, pp. 1601-1608.
IEEE DOI Link 0606
BibRef

Weinberger, K.Q.[Kilian Q.], Saul, L.K.[Lawrence K.],
Unsupervised Learning of Image Manifolds by Semidefinite Programming,
IJCV(70), No. 1, October 2006, pp. 77-90.
Springer DOI Link 0606
BibRef
Earlier: CVPR04(II: 988-995).
IEEE Abstract. IEEE Top Reference. 0408
Analyze high dimensional data. BibRef

Renzullo, L.J., Blanchfield, A.L., Powell, K.S.,
A Method of Wavelength Selection and Spectral Discrimination of Hyperspectral Reflectance Spectrometry,
GeoRS(44), No. 7, Part 2, July 2006, pp. 1986-1994.
IEEE DOI Link 0606
BibRef

Kim, J.W.[Jaeh-Wan], Choi, S.J.[Seung-Jin],
Semidefinite spectral clustering,
PR(39), No. 11, November 2006, pp. 2025-2035.
WWW Version. 0608
Convex optimization; Multi-way graph equipartitioning; Semidefinite programming; Spectral clustering BibRef

Berge, A.[Asbjørn], Solberg, A.S.[Anne Schistad],
Structured Gaussian Components for Hyperspectral Image Classification,
GeoRS(44), No. 11, November 2006, pp. 3386-3396.
IEEE DOI Link 0611
BibRef

Berge, A.[Asbjrn], Jensen, A.C.[Are C.], Solberg, A.H.S.[Anne H. Schistad],
Sparse Inverse Covariance Estimates for Hyperspectral Image Classification,
GeoRS(45), No. 5, May 2007, pp. 1399-1407.
IEEE DOI Link 0704
BibRef
Earlier: A1, A3, Only:
Sparse Covariance Estimates for High Dimensional Classification Using the Cholesky Decomposition,
SSPR06(835-843).
Springer DOI Link 0608
BibRef

Jensen, A.C.[Are C.], Berge, A.[Asbjrn], Solberg, A.H.S.[Anne H. Schistad],
Regression Approaches to Small Sample Inverse Covariance Matrix Estimation for Hyperspectral Image Classification,
GeoRS(46), No. 10, October 2008, pp. 2814-2822.
IEEE DOI Link 0810
BibRef

Jimenez-Rodriguez, L.O., Arzuaga-Cruz, E., Velez-Reyes, M.,
Unsupervised Linear Feature-Extraction Methods and Their Effects in the Classification of High-Dimensional Data,
GeoRS(45), No. 2, February 2007, pp. 469-483.
IEEE DOI Link 0703
BibRef

Serpico, S.B., Moser, G.,
Extraction of Spectral Channels From Hyperspectral Images for Classification Purposes,
GeoRS(45), No. 2, February 2007, pp. 484-495.
IEEE DOI Link 0703
BibRef

Santurri, L.[Leonardo],
Aliasing assessment in wavelength domain of hyperspectral data,
RealTimeIP(1), No. 2, December 2006, pp. 131-141.
Springer DOI Link 0001
BibRef

Rud, R.[Ronit], Shoshany, M.[Maxim], Alchanatis, V.[Victor], Cohen, Y.[Yafit],
Application of spectral features' ratios for improving classification in partially calibrated hyperspectral imagery: a case study of separating Mediterranean vegetation species,
RealTimeIP(1), No. 2, December 2006, pp. 143-152.
Springer DOI Link 0001
BibRef

Kogan, J.[Jacob],
Introduction to Clustering Large and High-Dimensional Data,
Cambridge University Press2006. ISBN-13: 9780521852678
WWW Version. Or:
WWW Version. Focused coverage of a few important algorithms. BibRef 0600

Monteiro, S.T.[Sildomar Takahashi], Minekawa, Y.[Yohei], Kosugi, Y.[Yukio], Akazawa, T.[Tsuneya], Oda, K.[Kunio],
Prediction of sweetness and amino acid content in soybean crops from hyperspectral imagery,
PandRS(62), No. 1, May 2007, pp. 2-12.
WWW Version. 0709
Agriculture; Hyperspectral image; Modeling; Neural networks; Spatial prediction BibRef

Dehaan, R.[Remy], Louis, J.[John], Wilson, A.[Andrea], Hall, A.[Andrew], Rumbachs, R.[Rod],
Discrimination of blackberry (Rubus fruticosus sp. agg.) using hyperspectral imagery in Kosciuszko National Park, NSW, Australia,
PandRS(62), No. 1, May 2007, pp. 13-24.
WWW Version. 0709
Hyperspectral imagery; Weeds; Blackberry; Ecosystem management BibRef

Zhao, D.H.[De-Hua], Huang, L.[Liangmei], Li, J.L.[Jian-Long], Qi, J.[Jiaguo],
A comparative analysis of broadband and narrowband derived vegetation indices in predicting LAI and CCD of a cotton canopy,
PandRS(62), No. 1, May 2007, pp. 25-33.
WWW Version. 0709
Hyperspectral remote sensing; Cotton; Broadband vegetation indices; Narrowband VIs; Leaf area index (LAI); Canopy chlorophyll density (CCD); Bandwidth and wavelength selection BibRef

Hsu, P.H.[Pai-Hui],
Feature extraction of hyperspectral images using wavelet and matching pursuit,
PandRS(62), No. 2, June 2007, pp. 78-92.
WWW Version. 0709
Hyperspectral remote sensing; Wavelet transform; Feature extraction; Matching pursuit; Classification BibRef

Vaiphasa, C.[Chaichoke], Skidmore, A.K.[Andrew K.], de Boer, W.F.[Willem F.], Vaiphasa, T.[Tanasak],
A hyperspectral band selector for plant species discrimination,
PandRS(62), No. 3, August 2007, pp. 225-235.
WWW Version. 0709
Artificial_Intelligence; Classification; Hyper spectral; Mangrove; Remote sensing; Vegetation BibRef

Wang, S., Chang, C.I.,
Variable-Number Variable-Band Selection for Feature Characterization in Hyperspectral Signatures,
GeoRS(45), No. 9, September 2007, pp. 2979-2992.
IEEE DOI Link 0710
BibRef

Ball, J.E., Bruce, L.M.,
Level Set Hyperspectral Image Classification Using Best Band Analysis,
GeoRS(45), No. 10, October 2007, pp. 3022-3027.
IEEE DOI Link 0711
BibRef

Kasapoglu, N.G., Ersoy, O.K.,
Border Vector Detection and Adaptation for Classification of Multispectral and Hyperspectral Remote Sensing Images,
GeoRS(45), No. 12, December 2007, pp. 3880-3893.
IEEE DOI Link 0711
BibRef

Bali, N., Mohammad-Djafari, A.,
Bayesian Approach With Hidden Markov Modeling and Mean Field Approximation for Hyperspectral Data Analysis,
IP(17), No. 2, February 2008, pp. 217-225.
IEEE DOI Link 0801
BibRef

Bali, N., Mohammad-Djafari, A., Mohammadpoor, A.,
Joint Dimensionality Reduction, Classification and Segmentation of Hyperspectral Images,
ICIP06(969-972). 0610

IEEE DOI Link BibRef

Guo, B.F.[Bao-Feng], Damper, R.I., Gunn, S.R.[Steve R.], Nelson, J.D.B.,
A fast separability-based feature-selection method for high-dimensional remotely sensed image classification,
PR(41), No. 5, May 2008, pp. 1670-1679.
WWW Version. 0711
Feature selection; Mutual information; Remote sensing; Hyperspectral image classification BibRef

Guo, B.F.[Bao-Feng], Gunn, S.R.[Steve R.], Damper, R.I., Nelson, J.D.B.,
Customizing Kernel Functions for SVM-Based Hyperspectral Image Classification,
IP(17), No. 4, April 2008, pp. 622-629.
IEEE DOI Link 0803
BibRef

Galvao, L.S.[Lenio Soares], Formaggio, A.R.[Antonio Roberto], Couto, E.G.[Eduardo Guimaraes], Roberts, D.A.[Dar A.],
Relationships between the mineralogical and chemical composition of tropical soils and topography from hyperspectral remote sensing data,
PandRS(63), No. 2, March 2008, pp. 259-271.
WWW Version. 0803
Hyperspectral remote sensing; Tropical soils; AVIRIS; Topography; Mineral identification BibRef

Prasad, S., Bruce, L.M.,
Decision Fusion With Confidence-Based Weight Assignment for Hyperspectral Target Recognition,
GeoRS(46), No. 5, May 2008, pp. 1448-1456.
IEEE DOI Link 0804
BibRef

Orlov, N.[Nikita], Shamir, L.[Lior], Macura, T.[Tomasz], Johnston, J.[Josiah], Eckley, D.M.[D. Mark], Goldberg, I.G.[Ilya G.],
Wnd-charm: Multi-purpose image classification using compound image transforms,
PRL(29), No. 11, 1 August 2008, pp. 1684-1693.
WWW Version. 0804
Image classification; Biological imaging; Image features; High dimensional classification BibRef

Chang, C.I.[Chein-I], Chakravarty, S.[Sumit], Chen, H.M.[Hsian-Min], Ouyang, Y.C.[Yen-Chieh],
Spectral derivative feature coding for hyperspectral signature analysis,
PR(42), No. 3, March 2009, pp. 395-408.
WWW Version. 0811
Spectral analysis manager (SPAM); Spectral derivative feature coding (SDFC); Spectral feature-based binary coding (SFBC) BibRef

Qiu, F.[Fang],
Neuro-fuzzy Based Analysis of Hyperspectral Imagery,
PhEngRS(74), No. 10, October 2008, pp. 1235-1248.
WWW Version. 0804
A neuro-fuzzy system, namely Gaussian Fuzzy Learning Vector Quantization, was developed to efficiently and effectively analyze hyperspectral data. BibRef

Eddy, P.R., Smith, A.M., Hill, B.D., Peddle, D.R., Coburn, C.A., Blackshaw, R.E.,
Hybrid Segmentation: Artificial Neural Network Classification of High Resolution Hyperspectral Imagery for Site-Specific Herbicide Management in Agriculture,
PhEngRS(74), No. 10, October 2008, pp. 1249-1258.
WWW Version. 0804
A new, efficient AI method is presented for improved weed management in crops with significant economic and environmental advantages. BibRef

Zhang, Q.A.[Qi-Ang], Wang, H.[Han], Plemmons, R.J.[Robert J.], Pauca, V.P.[V. Paul],
Tensor methods for hyperspectral data analysis: A space object material identification study,
JOSA-A(25), No. 12, December 2008, pp. 3001-3012.
WWW Version. 0804
BibRef

Liu, X.W.[Xiu-Wen], Zhang, Q.A.[Qi-Ang],
Spectral histogram representations for visual modeling,
AIPR03(199-204).
IEEE DOI Link 0310
BibRef

Zhong, P., Wang, R.,
Learning Sparse CRFs for Feature Selection and Classification of Hyperspectral Imagery,
GeoRS(46), No. 12, December 2008, pp. 4186-4197.
IEEE DOI Link 0812
BibRef

Chen, J., Jia, X., Yang, W., Matsushita, B.,
Generalization of Subpixel Analysis for Hyperspectral Data With Flexibility in Spectral Similarity Measures,
GeoRS(47), No. 7, July 2009, pp. 2165-2171.
IEEE DOI Link 0906
BibRef

Plaza, J.[Javier], Plaza, A.[Antonio], Perez, R.[Rosa], Martinez, P.[Pablo],
On the use of small training sets for neural network-based characterization of mixed pixels in remotely sensed hyperspectral images,
PR(42), No. 11, November 2009, pp. 3032-3045.
Elsevier DOI Link
WWW Version. 0907
Hyperspectral; Image processing; Mixed pixels; Spectral mixture analysis; Multi-layer perceptron; Automatic training sample generation algorithms; Mixed training samples; Nonlinear spectral unmixing BibRef

Hinnrichs, M., Gupta, N., Goldberg, A.,
Dual band (MWIR/LWIR) hyperspectral imager,
AIPR03(73-78).
IEEE DOI Link 0310
BibRef

Gupta, N.,
Fused spectropolarimetric visible near-IR imaging,
AIPR03(21-26).
IEEE DOI Link 0310
BibRef

Gupta, N., Smith, D.,
A field-portable simultaneous dual-band infrared hyperspectral imager,
AIPR05(87-92).
IEEE DOI Link 0510
BibRef

Ramanath, R., Snyder, W.E., Qi, H.R.[Hai-Rong],
Eigenviews for object recognition in multispectral imaging systems,
AIPR03(33-38).
IEEE DOI Link 0310
BibRef

Du, H.T.[Hong-Tao], Qi, H.R.[Hai-Rong], Wang, X.L.[Xiao-Ling], Ramanath, R., Snyder, W.E.,
Band selection using independent component analysis for hyperspectral image processing,
AIPR03(93-98).
IEEE DOI Link 0310
BibRef

Schaum, A.P., Stocker, A.,
Advanced algorithms for autonomous hyperspectral change detection,
AIPR04(33-38).
IEEE DOI Link 0410
BibRef

Schaum, A.P.,
Adapting to Change: The CFAR Problem in Advanced Hyperspectral Detection,
AIPR07(15-21).
IEEE DOI Link 0710
BibRef

Schaum, A.P.,
Autonomous Hyperspectral Target Detection with Quasi-Stationarity Violation at Background Boundaries,
AIPR06(16-16).
IEEE DOI Link 0610
BibRef
Earlier:
Hyperspectral detection algorithms: operational, next generation, on the horizon,
AIPR05(72-80).
IEEE DOI Link 0510
BibRef
Earlier:
Matched affine joint subspace detection in remote hyperspectral reconnaissance,
AIPR02(13-18).
IEEE DOI Link 0210
BibRef

Schaum, A.P.,
Data association for fusion in spatial and spectral imaging,
AIPR03(87-92).
IEEE DOI Link 0310
BibRef

Shah, C.A., Arora, M.K., Robila, S.A., Varshney, P.K.,
ICA mixture model based unsupervised classification of hyperspectral imagery,
AIPR02(29-35).
IEEE DOI Link 0210
BibRef

Schott, J.R., Lee, K., Raqueno, R., Hoffmann, G.,
Use of physics based models in hyperspectral image exploitation,
AIPR02(36-42).
IEEE DOI Link 0210
BibRef

Muhammed, H.H.,
Unsupervised hyperspectral image segmentation using a new class of neuro-fuzzy systems based on weighted incremental neural networks,
AIPR02(171-177).
IEEE DOI Link 0210
BibRef
And:
Using hyperspectral reflectance data for discrimination between healthy and diseased plants, and determination of damage-level in diseased plants,
AIPR02(49-54).
IEEE DOI Link 0210
BibRef

Dombrowski, M., Bajaj, J., Willson, P.,
Video-rate visible to LWIR hyperspectral imaging and image exploitation,
AIPR02(178-185).
IEEE DOI Link 0210
BibRef

Zare, A.[Alina], Gader, P.D.[Paul D.],
Endmember detection using the Dirichlet process,
ICPR08(1-4).
IEEE DOI Link 0812
feature reduction for hyperspectral data BibRef

Streeter, L., Burling-Claridge, G.R., Cree, M.J., Kunnemeyer, R.,
Comparison of Hadamard imaging and compressed sensing for low resolution hyperspectral imaging,
IVCNZ08(1-6).
IEEE DOI Link 0811
BibRef

Sato, M.[Maiko], Kudo, M.[Mineichi], Toyama, J.[Jun],
Behavior Analysis of Volume Prototypes in High Dimensionality,
SSPR08(874-884).
Springer DOI Link 0812
BibRef

Yang, H., Wang, Q., He, Z.,
Indexing Sub-Vector Distance for High-Dimensional Feature Matching,
BMVC08(xx-yy).
PDF Version. 0809
BibRef

Martínez-Usó, A.[Adolfo], Pla, F.[Filiberto], Martínez Sotoca, J.[José], García-Sevilla, P.[Pedro],
From Narrow to Broad Band Design and Selection in Hyperspectral Images,
ICIAR08(xx-yy).
Springer DOI Link 0806
BibRef
Earlier:
Comparison of Unsupervised Band Selection Methods for Hyperspectral Imaging,
IbPRIA07(I: 30-38).
Springer DOI Link 0706
BibRef

Berge, A.[Asbjørn], Solberg, A.S.[Anne Schistad],
Improving Hyperspectral Classifiers: The Difference Between Reducing Data Dimensionality and Reducing Classifier Parameter Complexity,
SCIA07(293-302).
Springer DOI Link 0706
BibRef

Gupta, M.R., Jacobson, N.P.,
Wavelet Principal Component Analysis and its Application to Hyperspectral Images,
ICIP06(1585-1588). 0610

IEEE DOI Link BibRef

Bakir, T., Peter, A.M., Riley, R., Hackett, J.,
Non-Negative Maximum Likelihood ICA for Blind Source Separation of Images and Signals with Application to Hyperspectral Image Subpixel Demixing,
ICIP06(3237-3240). 0610

IEEE DOI Link BibRef

Ferreiro-Armán, M., da Costa, J.P., Homayouni, S., Martín-Herrero, J.,
Hyperspectral Image Analysis for Precision Viticulture,
ICIAR06(II: 730-741).
Springer DOI Link 0610
BibRef

Borges, J.S.[Janete S.], Bioucas-Dias, J.M.[José M.], Marçal, A.R.S.[André R. S.],
Fast Sparse Multinomial Regression Applied to Hyperspectral Data,
ICIAR06(II: 700-709).
Springer DOI Link 0610
BibRef

Marçal, A.R.S.[André R.S.], Borges, J.S.[Janete S.],
Estimating the Natural Number of Classes on Hierarchically Clustered Multi-spectral Images,
ICIAR05(447-455).
Springer DOI Link 0509
BibRef

Rothaus, K.[Kai], Jiang, X.Y.[Xiao-Yi], Lambers, M.[Martin],
Comparison of Methods for Hyperspherical Data Averaging and Parameter Estimation,
ICPR06(III: 395-399).
WWW Version. 0609
BibRef

Nascimento, J.M.P.[José M.P.], Dias, J.M.B.[José M.B.],
Signal Subspace Identification in Hyperspectral Linear Mixtures,
IbPRIA05(II:207).
Springer DOI Link 0509
BibRef

Zeng, H.W.[Hui-Wen], Trussell, H.J.,
Feature Selection using a Mixed-Norm Penalty Function,
ICIP06(997-1000). 0610

IEEE DOI Link BibRef
Earlier:
Dimensionality reduction in hyperspectral image classification,
ICIP04(II: 913-916).
IEEE DOI Link 0505
BibRef

Sarkar, S., Healey, G.,
Hyperspectral texture classification using generalized Markov fields,
CVPR04(I: 429-434).
IEEE Abstract. IEEE Top Reference. 0408
BibRef

Yu, S.X., Shi, J.B.[Jian-Bo],
Multiclass spectral clustering,
ICCV03(313-319).
IEEE DOI Link 0311
BibRef

Gomez Chova, L., Calpe, J., Soria, E., Camps Valls, G., Martin, J.D., Moreno, J.,
Cart-based feature selection of hyperspectral images for crop cover classification,
ICIP03(III: 589-592).
IEEE Abstract. IEEE Top Reference. 0312
BibRef

Gu, Y.F.[Yan-Feng], Zhang, Y.[Ye],
Unsupervised subspace linear spectral mixture analysis for hyperspectral images,
ICIP03(I: 801-804).
IEEE Abstract. IEEE Top Reference. 0312
BibRef

Gu, Y.F.[Yan-Feng], Zhang, Y.[Ye], Zhang, J.,
A kernel based nonlinear subspace projection method for reduction of hyperspectral, image dimensionality,
ICIP02(II: 357-360).
IEEE Abstract. IEEE Top Reference. 0210
BibRef

Muhammed, H.H., Ammenberg, P., Bengtsson, E.,
Using feature-vector based analysis, based on principal component analysis and independent component analysis, for analysing hyperspectral images,
CIAP01(309-315).
IEEE Top Reference. 0210
BibRef

You, H., Chang, E.,
Spin Discriminant Analysis(SDA): Using A One-Dimensional Classifier for High Dimensional Classification Problems,
CVPR01(I:968-975).
IEEE Abstract. IEEE Top Reference. 0110
Using a simpler classifier to deal with harder (high-dimensional) problems. BibRef

Peng, J.[Jing], Heisterkamp, D.R.[Douglas R.], Dai, H.K.,
LDA/SVM Driven Nearest Neighbor Classification,
CVPR01(I:58-63).
IEEE Abstract. IEEE Top Reference. 0110
With high dimensions and limited samples. Neighbor morphing to eliminate the bias due to high dimensions. BibRef

Muto, Y., Nagase, H., Hamamoto, Y.,
Evaluation of a Modified Parzen Classifier in High Dimensional Spaces,
ICPR00(Vol II: 67-70).
IEEE DOI Link
HTML Version. 0009
BibRef

Mostafa, M.G.H., Perkins, T.C., Farag, A.A.,
A Two-step Fuzzy-bayesian Classification for High Dimensional Data,
ICPR00(Vol III: 417-420).
IEEE DOI Link
HTML Version. 0009
BibRef

Mostafa, M.G.H., Perkins, T.C., Farag, A.A.,
Supervised Fuzzy and Bayesian Classification of High Dimensional Data: a Comparative Study,
ICIP00(Vol I: 772-775).
IEEE Abstract. IEEE Top Reference. 0008
BibRef

Zhang, J., Zhang, Y., Zou, B., Zhou, T.,
Fusion Classification of Hyperspectral Image Based on Adaptive Subspace Decomposition,
ICIP00(Vol III: 472-475).
IEEE Abstract. IEEE Top Reference. 0008
BibRef

Zhang, Y.[Ye], Desai, M.D.[Mita D.],
Adaptive Subspace Decomposition for Hyperspectral Data Dimensionality Reduction,
ICIP99(II:326-329).
IEEE Abstract. IEEE Top Reference. BibRef 9900

Wu, S.G.[Shu-Guang], Desai, M.D.[Mita D.],
Adaptive tree-structured subspace classification of hyperspectral images,
ICIP98(I: 570-573).
IEEE DOI Link 9810
BibRef

Bajic, S.C.,
Accuracy of a supervised classification of the artificial objects in thermal hyperspectral images,
CIAP99(798-803).
IEEE DOI Link 9909
BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Hyperspectral Data Anomaly Detection, Hyper-Spectral Anomaly .