C. M. Bachmann, T. L. Ainsworth, and R. A. Fusina, Exploiting manifold geometry in hyperspectral imagery, IEEE Transactions on Geoscience and Remote Sensing, vol.43, issue.3, pp.441-454, 2005.
DOI : 10.1109/TGRS.2004.842292

P. Bajcsy and P. Groves, Methodology for hyperspectral band selection Photogrammetric engineering and remote sensing, pp.793-802, 2004.

M. Beauchemin and K. B. Fung, On statistical band selection for image visualization Photogrammetric engineering and remote sensing, pp.571-574, 2001.

A. J. Bell, The co-information lattice, Proceedings of the Fifth International Workshop on Independent Component Analysis and Blind Signal Separation, 2003.

A. J. Bell and T. J. Sejnowski, An Information-Maximization Approach to Blind Separation and Blind Deconvolution, Neural Computation, vol.20, issue.1, pp.1129-1159, 1995.
DOI : 10.1109/78.301850

N. D. Bruce and J. K. Tsotsos, Saliency, attention, and visual search: An information theoretic approach, Journal of Vision, vol.9, issue.3, 2009.
DOI : 10.1167/9.3.5

G. Buchsbaum and A. Gottschalk, Trichromacy, Opponent Colours Coding and Optimum Colour Information Transmission in the Retina, Proceedings of the Royal society of London. Series B. Biological sciences, pp.89-113, 1218.
DOI : 10.1098/rspb.1983.0090

S. Cai, Q. Du, and R. Moorhead, Hyperspectral imagery visualization using double layers, IEEE Transactions on Geoscience and Remote Sensing, vol.45, issue.10, pp.3028-3036, 2007.

S. Cai, Q. Du, and R. J. Moorhead, Feature-Driven Multilayer Visualization for Remotely Sensed Hyperspectral Imagery, IEEE Transactions on Geoscience and Remote Sensing, vol.48, issue.9, pp.3471-3481, 2010.
DOI : 10.1109/TGRS.2010.2047021

C. Cariou, K. Chehdi, and S. Le-moan, BandClust: An Unsupervised Band Reduction Method for Hyperspectral Remote Sensing, IEEE Geoscience and Remote Sensing Letters, vol.8, issue.3, pp.564-568, 2010.
DOI : 10.1109/LGRS.2010.2091673
URL : https://hal.archives-ouvertes.fr/hal-00946927

M. Cerf, J. Harel, W. Einhäuser, and C. Koch, Predicting human gaze using low-level saliency combined with face detection Advances in neural information processing systems, pp.241-248, 2008.

C. I. Chang and Q. Du, Interference and noise-adjusted principal components analysis, IEEE Transactions on Geoscience and Remote Sensing, vol.37, issue.5, pp.2387-2396, 1999.
DOI : 10.1109/36.789637

C. I. Chang and S. Wang, Constrained band selection for hyperspectral imagery, IEEE Transactions on Geoscience and Remote Sensing, vol.44, issue.6, pp.1575-1585, 2006.
DOI : 10.1109/TGRS.2006.864389

C. I. Chang, T. L. Sun, and M. L. Althouse, Unsupervised interference rejection approach to target detection and classification for hyperspectral imagery, Optical Engineering, vol.37, issue.3, p.735, 1998.
DOI : 10.1117/1.601905

C. I. Chang, Q. Du, T. L. Sun, and M. L. Althouse, A joint band prioritization and band-decorrelation approach to band selection for hyperspectral image classification, IEEE Transactions on Geoscience and Remote Sensing, vol.37, issue.6, pp.2631-2641, 1999.
DOI : 10.1109/36.803411

P. Chavez, L. Berlin, and . Sowers, Statistical method for selecting landsat mss ratios, Journal of Applied Photographic Engineering, vol.8, issue.1, pp.23-30, 1982.

H. Chen and P. K. Varshney, A human perception inspired quality metric for image fusion based on regional information, Information Fusion, vol.8, issue.2, pp.193-207, 2007.
DOI : 10.1016/j.inffus.2005.10.001

Y. Chen and R. S. Blum, A new automated quality assessment algorithm for image fusion, Image and Vision Computing, vol.27, issue.10, pp.1421-1432, 2009.
DOI : 10.1016/j.imavis.2007.12.002

M. Cui, A. Razdan, J. Hu, and P. Wonka, Interactive hyperspectral image visualization using convex optimization, IEEE Transactions on Geoscience and Remote Sensing, issue.6, p.471673, 2009.

N. Cvejic, D. Canagarajah, and . Bull, Image fusion metric based on mutual information and Tsallis entropy, Electronics Letters, vol.42, issue.11, pp.626-627, 2006.
DOI : 10.1049/el:20060693

M. D. Mura, A. Villa, J. A. Benediktsson, J. Chanussot, and L. Bruzzone, Classification of hyperspectral images by using extended morphological attribute profiles and independent component analysis, IEEE Transactions on Geoscience and Remote Sensing Letters, issue.99, pp.541-545, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00578886

B. Demir, A. Celebi, and S. Erturk, A Low-Complexity Approach for the Color Display of Hyperspectral Remote-Sensing Images Using One-Bit-Transform-Based Band Selection, IEEE Transactions on Geoscience and Remote Sensing, vol.47, issue.1, pp.97-105, 2009.
DOI : 10.1109/TGRS.2008.2001553

H. Du, H. Qi, X. Wang, R. Ramanath, and W. E. Snyder, Band selection using independent component analysis for hyperspectral image processing, Applied Imagery Pattern Recognition Workshop Proceedings. 32nd, pp.93-98, 2003.

Q. Du, Band selection and its impact on target detection and classification in hyperspectral image analysis, Workshop on Advances in Techniques for Analysis of Remotely Sensed Data, pp.374-377, 2003.

Q. Du and H. Yang, Similarity-Based Unsupervised Band Selection for Hyperspectral Image Analysis, IEEE Geoscience and Remote Sensing Letters, vol.5, issue.4, pp.564-568, 2008.
DOI : 10.1109/LGRS.2008.2000619

Q. Du, H. Ren, and C. I. Chang, A comparative study for orthogonal subspace projection and constrained energy minimization, IEEE Transactions on Geoscience and Remote Sensing, issue.6, pp.411525-1529, 2003.

Q. Du, N. Raksuntorn, S. Cai, and R. J. Moorhead, Color Display for Hyperspectral Imagery, IEEE Transactions on Geoscience and Remote Sensing, vol.46, issue.6, pp.1858-1866, 2008.
DOI : 10.1109/TGRS.2008.916203

M. Fauvel, J. Chanussot, and J. A. Benediktsson, Kernel Principal Component Analysis for Feature Reduction in Hyperspectrale Images Analysis, Proceedings of the 7th Nordic Signal Processing Symposium, NORSIG 2006, pp.238-241, 2006.
DOI : 10.1109/NORSIG.2006.275232

D. H. Foster, S. Nascimento, and K. Amano, Information limits on neural identification of colored surfaces in natural scenes, Visual Neuroscience, vol.21, issue.03, pp.331-336, 2004.
DOI : 10.1017/S0952523804213335

J. H. Friedman and J. W. Tukey, A Projection Pursuit Algorithm for Exploratory Data Analysis, IEEE Transactions on Computers, vol.23, issue.9, pp.881-890, 1974.
DOI : 10.1109/T-C.1974.224051

S. Frintrop, E. Rome, and H. I. Christensen, Computational visual attention systems and their cognitive foundations, ACM Transactions on Applied Perception, vol.7, issue.1, p.6, 2010.
DOI : 10.1145/1658349.1658355

D. Gao, V. Mahadevan, and N. Vasconcelos, On the plausibility of the discriminant center-surround hypothesis for visual saliency, Journal of Vision, vol.8, issue.7, 2008.
DOI : 10.1167/8.7.13

W. R. Garner, Uncertainty and structure as psychological concepts, 1962.

S. Goferman, L. Zelnik-manor, and A. Tal, Context-aware saliency detection, Conference on Computer Vision and Pattern Recognition, pp.2376-2383, 2010.

R. C. Gonzalez, R. E. Woods, and S. L. Eddins, Digital image processing using MATLAB, 2004.

J. Granahan and J. Sweet, An evaluation of atmospheric correction techniques using the spectral similarity scale IGARSS'01, IEEE Geoscience and Remote Sensing Symposium, pp.2022-2024, 2001.

H. Grassmann, On the theory of compound colors, Philosophical Magazine, vol.7, pp.254-64, 1854.

A. A. Green, M. Berman, P. Switzer, and M. D. Craig, A transformation for ordering multispectral data in terms of image quality with implications for noise removal, IEEE Transactions on Geoscience and Remote Sensing, vol.26, issue.1, pp.65-74, 1988.
DOI : 10.1109/36.3001

T. Han and D. G. Goodenough, Investigation of Nonlinearity in Hyperspectral Imagery Using Surrogate Data Methods, IEEE Transactions on Geoscience and Remote Sensing, vol.46, issue.10, pp.2840-2847, 2008.
DOI : 10.1109/TGRS.2008.2002952

J. Y. Hardeberg, Acquisition and reproduction of color images: colorimetric and multispectral approaches, 2001.

J. Harel, C. Koch, and P. Perona, Graph-based visual saliency Advances in neural information processing systems, p.545, 2007.

D. C. Heinz and C. I. Chang, Fully constrained least squares linear spectral mixture analysis method for material quantification in hyperspectral imagery, IEEE Transactions on Geoscience and Remote Sensing, vol.39, issue.3, pp.529-545, 2001.
DOI : 10.1109/36.911111

J. P. Hoffbeck and D. A. Landgrebe, Effect of radiance-to-reflectance transformation and atmosphere removal on maximum likelihood classification accuracy of high-dimensional remote sensing data, Proceedings of IGARSS '94, 1994 IEEE International Geoscience and Remote Sensing Symposium, pp.2538-2540, 1994.
DOI : 10.1109/IGARSS.1994.399791

M. Hossny, S. Nahavandi, and D. Creighton, Comments on ???Information measure for performance of image fusion???, Electronics Letters, vol.44, issue.18, pp.1066-1067, 2008.
DOI : 10.1049/el:20081754

M. Hossny, S. Nahavandi, D. Creighton, and A. Bhatti, Image fusion performance metric based on mutual information and entropy driven quadtree decomposition, Electronics Letters, vol.46, issue.18, pp.461266-1268, 2010.
DOI : 10.1049/el.2010.1778

X. Hou and L. Zhang, Saliency Detection: A Spectral Residual Approach, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007.
DOI : 10.1109/CVPR.2007.383267

X. Hou, J. Harel, and C. Koch, Image signature: Highlighting sparse salient regions, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011.

P. J. Huber, Projection pursuit. The annals of Statistics, pp.435-475, 1985.

A. Hyvärinen, New approximations of differential entropy for independent component analysis and projection pursuit, Neural Information Processing Systems, pp.273-279, 1998.

A. Hyvärinen and E. Oja, A Fast Fixed-Point Algorithm for Independent Component Analysis, Neural Computation, vol.9, issue.7, pp.1483-1492, 1997.
DOI : 10.1109/18.212280

A. Hyvärinen and E. Oja, Independent component analysis: algorithms and applications, Neural Networks, vol.13, issue.4-5, pp.411-430, 2000.
DOI : 10.1016/S0893-6080(00)00026-5

A. Ibrahim, S. Tominaga, and T. Horiuchi, Invariant representation for spectral reflectance images and its application, EURASIP Journal on Image and Video Processing, vol.2011, issue.1, p.2011, 2011.
DOI : 10.2352/J.ImagingSci.Technol.2010.54.4.040502

A. Ifarraguerri and C. I. Chang, Unsupervised hyperspectral image analysis with projection pursuit, IEEE Transactions on Geoscience and Remote Sensing, vol.38, issue.6, pp.2529-2538, 2000.

F. H. Imai, M. R. Rosen, and R. S. Berns, Comparative study of metrics for spectral match quality, Proceedings of the First European Conference on Colour in Graphics, Imaging and Vision, pp.492-496, 2002.

L. Itti, C. Koch, and E. Niebur, A model of saliency-based visual attention for rapid scene analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.20, issue.11, pp.1254-1259, 1998.
DOI : 10.1109/34.730558

N. P. Jacobson and M. R. Gupta, Design goals and solutions for display of hyperspectral images, IEEE Transactions on Geoscience and Remote Sensing, vol.43, issue.11, pp.2684-2692, 2005.
DOI : 10.1109/TGRS.2005.857623

N. P. Jacobson, M. R. Gupta, and J. B. Cole, Linear Fusion of Image Sets for Display, IEEE Transactions on Geoscience and Remote Sensing, vol.45, issue.10, pp.453277-3288, 2007.
DOI : 10.1109/TGRS.2007.903598

A. Jakulin and I. Bratko, Quantifying and visualizing attribute interactions: An approach based on entropy. Arxiv preprint cs, p.308002, 2004.

X. Jia and J. Richards, Segmented principal components transformation for efficient hyperspectral remote-sensing image display and classification, IEEE Transactions on Geoscience and Remote Sensing, vol.37, issue.1, pp.538-542, 1999.

L. Jimenez and D. Landgrebe, Supervised classification in high-dimensional space: geometrical, statistical, and asymptotical properties of multivariate data, IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), vol.28, issue.1, pp.39-54, 1998.
DOI : 10.1109/5326.661089

T. Judd, K. Ehinger, F. Durand, and A. Torralba, Learning to predict where humans look, 2009 IEEE 12th International Conference on Computer Vision, pp.2106-2113, 2009.
DOI : 10.1109/ICCV.2009.5459462

C. Jutten and J. Herault, Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture, Signal Processing, vol.24, issue.1, pp.1-10, 1991.
DOI : 10.1016/0165-1684(91)90079-X

S. Kaewpijit, J. L. Moigne, and T. El-ghazawi, Automatic reduction of hyperspectral imagery using wavelet spectral analysis, IEEE Transactions on Geoscience and Remote Sensing, vol.41, issue.4, pp.863-871, 2003.
DOI : 10.1109/TGRS.2003.810712

C. Koch and S. Ullman, Shifts in Selective Visual Attention: Towards the Underlying Neural Circuitry, Human neurobiology, vol.4, issue.4, pp.219-246, 1985.
DOI : 10.1007/978-94-009-3833-5_5

T. O. Kvalseth, Entropy and Correlation: Some Comments, IEEE Transactions on Systems, Man, and Cybernetics, vol.17, issue.3, pp.517-519, 1987.
DOI : 10.1109/TSMC.1987.4309069

A. Steven-le-moan, Y. Mansouri, J. Y. Voisin, and . Hardeberg, Visualisation d'images spectrales : une méthode basée sur la perception humaine, Proceedings of ORASIS, 2011.

A. Steven-le-moan, Y. Mansouri, J. Y. Voisin, and . Hardeberg, A Constrained Band Selection Method Based on Information Measures for Spectral Image Color Visualization, IEEE Transactions on Geoscience and Remote Sensing, vol.49, issue.12, pp.5104-5115, 2011.
DOI : 10.1109/TGRS.2011.2158319

C. H. Lee, A. Varshney, and D. W. Jacobs, Mesh saliency, ACM SIGGRAPH 2005 Papers, p.666, 2005.

J. B. Lee, A. S. Woodyatt, and M. Berman, Enhancement of high spectral resolution remote-sensing data by a noise-adjusted principal components transform, IEEE Transactions on Geoscience and Remote Sensing, vol.28, issue.3, pp.295-304, 1990.
DOI : 10.1109/36.54356

M. Lennon, G. Mercier, L. Mc-mouchot, and . Hubert-moy, Independent component analysis as a tool for the dimensionality reduction and the representation of hyperspectral images, IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217), pp.2893-2895, 2001.
DOI : 10.1109/IGARSS.2001.978197

M. Lennon, G. Mercier, M. C. Mouchot, and L. Hubert-moy, Curvilinear component analysis for nonlinear dimensionality reduction of hyperspectral images. Image and Signal Processing for Remote Sensing VII, pp.157-168, 2001.

W. Lin, C. C. , and J. Kuo, Perceptual visual quality metrics: A survey, Journal of Visual Communication and Image Representation, vol.22, issue.4, pp.297-312, 2011.
DOI : 10.1016/j.jvcir.2011.01.005

Z. Liu, E. Blasch, Z. Xue, J. Zhao, R. Laganière et al., Objective Assessment of Multiresolution Image Fusion Algorithms for Context Enhancement in Night Vision: A Comparative Study, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.34, issue.1, pp.1-1, 2012.
DOI : 10.1109/TPAMI.2011.109

A. Mansouri, P. Marzani, and . Gouton, Neural networks in two cascade algorithms for spectral reflectance reconstruction, IEEE International Conference on Image Processing 2005, pp.718-721, 2005.
DOI : 10.1109/ICIP.2005.1530156

A. Martinez-uso, F. Pla, J. M. Sotoca, and P. Garcia-sevilla, Clusteringbased hyperspectral band selection using information measures, IEEE Transactions on Geoscience and Remote Sensing, issue.12, pp.454158-4171, 2007.

W. J. Mcgill, Multivariate information transmission, Psychometrika, vol.24, issue.2, pp.97-116, 1954.
DOI : 10.1007/BF02289159

M. Mignotte, A Multiresolution Markovian Fusion Model for the Color Visualization of Hyperspectral Images, IEEE Transactions on Geoscience and Remote Sensing, vol.48, issue.12, pp.4236-4247, 2010.
DOI : 10.1109/TGRS.2010.2051553

M. Mignotte, A Bicriteria-Optimization-Approach-Based Dimensionality-Reduction Model for the Color Display of Hyperspectral Images, IEEE Transactions on Geoscience and Remote Sensing, vol.50, issue.2, pp.1-13, 2012.
DOI : 10.1109/TGRS.2011.2160646

A. Mohan, G. Sapiro, and E. Bosch, Spatially Coherent Nonlinear Dimensionality Reduction and Segmentation of Hyperspectral Images, IEEE Geoscience and Remote Sensing Letters, vol.4, issue.2, pp.206-210, 2007.
DOI : 10.1109/LGRS.2006.888105

S. Moon and H. Qi, Hybrid dimensionality reduction method based on support vector machine and independent component analysis, IEEE Transactions on Neural Networks and Learning Systems, issue.99, pp.1-1, 2012.

J. M. Nascimento and J. M. Dias, Does independent component analysis play a role in unmixing hyperspectral data?, IEEE Transactions on Geoscience and Remote Sensing, vol.43, issue.1, pp.175-187, 2005.
DOI : 10.1109/TGRS.2004.839806

S. M. Nascimento, F. P. Ferreira, and D. H. Foster, Statistics of spatial cone-excitation ratios in natural scenes, Journal of the Optical Society of America A, vol.19, issue.8, pp.1484-1490, 2002.
DOI : 10.1364/JOSAA.19.001484

L. Parsons, E. Haque, and H. Liu, Subspace clustering for high dimensional data, ACM SIGKDD Explorations Newsletter, vol.6, issue.1, pp.90-105, 2004.
DOI : 10.1145/1007730.1007731

M. Pedersen and J. Y. Hardeberg, Full-reference image quality metrics: Classification and evaluation. Foundations and Trends R in Computer Graphics and Vision, pp.1-80, 2011.

A. M. Qaid and H. Basavarajappa, Application of optimum index factor technique to landsat-7 data for geological mapping of north east of Hajjah, Yemen. American-Eurasian Journal of Scientific Research, vol.3, issue.1, pp.84-91, 2008.

G. Qu, D. Zhang, and P. Yan, Information measure for performance of image fusion, Electronics Letters, vol.38, issue.7, p.313, 2002.
DOI : 10.1049/el:20020212

H. Ren and C. I. Chang, Automatic spectral target recognition in hyperspectral imagery, IEEE Transactions on Aerospace and Electronic Systems, vol.39, issue.4, pp.1232-1249, 2003.

N. Renard and S. Bourennane, Dimensionality Reduction Based on Tensor Modeling for Classification Methods, IEEE Transactions on Geoscience and Remote Sensing, vol.47, issue.4, pp.1123-1131, 2009.
DOI : 10.1109/TGRS.2008.2008903

P. Scheunders, Multispectral image fusion using local mapping techniques, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, pp.311-314, 2000.
DOI : 10.1109/ICPR.2000.906075

J. Serra, Image analysis and mathematical morphology, p.600, 1982.

C. E. Shannon and W. Weaver, A mathematical theory of communication . The Bell System Technical Journal, pp.379-423, 1948.

P. Sharma, F. A. Cheikh, and J. Y. Hardeberg, Saliency map for human gaze prediction in images, Sixteenth Color Imaging Conference, 2008.

C. Sheffield, Selecting band combinations from multispectral data, Photogrammetric Engineering and Remote Sensing, vol.51, pp.681-687, 1985.

C. Simon, U. Huxhagen, A. Mansouri, A. Heritage, F. Boochs et al., Integration of high-resolution spatial and spectral data acquisition systems to provide complementary datasets for cultural heritage applications, Computer Vision and Image Analysis of Art, p.75310, 2010.
DOI : 10.1117/12.838891
URL : https://hal.archives-ouvertes.fr/hal-00638588

L. I. Smith, A tutorial on principal components analysis, p.52, 2002.

M. Stokes, M. Anderson, S. Chandrasekar, and R. Motta, A standard default color space for the internet-srgb, 1996.

M. Studeny and J. Vejnarova, The multiinformation function as a tool for measuring stochastic dependence. Learning in graphical models, 1998.

K. Tiwari, D. Arora, and . Singh, An assessment of independent component analysis for detection of military targets from hyperspectral images, International Journal of Applied Earth Observation and Geoinformation, vol.13, issue.5, pp.730-740, 2011.
DOI : 10.1016/j.jag.2011.03.007

A. Toet, M. Hogervorst, . Sg-nikolov, . Lewis, . Td-dixon et al., Towards cognitive image fusion, Information Fusion, vol.11, issue.2, pp.95-113, 2010.
DOI : 10.1016/j.inffus.2009.06.008

A. M. Treisman and G. Gelade, A feature-integration theory of attention, Cognitive Psychology, vol.12, issue.1, pp.97-136, 1980.
DOI : 10.1016/0010-0285(80)90005-5

V. Tsagaris and V. Anastassopoulos, Information measure for assessing pixel-level fusion methods, Image and Signal Processing for Remote Sensing X, pp.64-71, 2004.
DOI : 10.1117/12.565597

V. Tsagaris and V. Anastassopoulos, Multispectral image fusion for improved RGB representation based on perceptual attributes, International Journal of Remote Sensing, vol.8, issue.15, pp.3241-3254, 2005.
DOI : 10.1016/S0165-1684(00)00273-5

V. Tsagaris, V. Anastassopoulos, and G. Lampropoulos, Fusion of hyperspectral data using segmented PCT for color representation and classification, IEEE Transactions on Geoscience and Remote Sensing, vol.43, issue.10, pp.432365-2375, 2005.
DOI : 10.1109/TGRS.2005.856104

J. S. Tyo, A. Konsolakis, D. I. Diersen, and R. C. Olsen, Principal-components-based display strategy for spectral imagery, IEEE Transactions on Geoscience and Remote Sensing, vol.41, issue.3, pp.708-718, 2003.
DOI : 10.1109/TGRS.2003.808879

L. Van-der-maaten, H. Eo-postma, . Van-den, and . Herik, Dimensionality reduction: A comparative review, pp.1-35, 2007.

J. Wang and C. I. Chang, Independent component analysis-based dimensionality reduction with applications in hyperspectral image analysis, IEEE Transactions on Geoscience and Remote Sensing, vol.44, issue.6, pp.1586-1600, 2006.
DOI : 10.1109/TGRS.2005.863297

P. Wang and B. Liu, A novel image fusion metric based on multiscale analysis, International Conference on Signal Processing, pp.965-968, 2008.

Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, Image Quality Assessment: From Error Visibility to Structural Similarity, IEEE Transactions on Image Processing, vol.13, issue.4, pp.600-612, 2004.
DOI : 10.1109/TIP.2003.819861

S. Watanabe, Information Theoretical Analysis of Multivariate Correlation, IBM Journal of Research and Development, vol.4, issue.1, pp.66-82, 1960.
DOI : 10.1147/rd.41.0066

T. A. Wilson, S. K. Rogers, and M. Kabrisky, Perceptual-based image fusion for hyperspectral data, IEEE Transactions on Geoscience and Remote Sensing, vol.35, issue.4, pp.1007-1017, 1997.
DOI : 10.1109/36.602543

W. Xia, X. Liu, B. Wang, and L. Zhang, Independent Component Analysis for Blind Unmixing of Hyperspectral Imagery With Additional Constraints, IEEE Transactions on Geoscience and Remote Sensing, vol.49, issue.6, pp.2165-2179, 2011.
DOI : 10.1109/TGRS.2010.2101609

C. Xydeas and V. Petrovic, Objective image fusion performance measure, Electronics Letters, vol.36, issue.4, pp.308-309, 2000.
DOI : 10.1049/el:20000267

H. Zhang, D. W. Messinger, and E. D. Montag, Perceptual display strategies of hyperspectral imagery based on PCA and ICA, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII, p.31, 2006.
DOI : 10.1117/12.665696

H. Zhang, H. Peng, M. D. Fairchild, and E. D. Montag, Hyperspectral image visualization based on a human visual model, Human Vision and Electronic Imaging XIII, p.68060, 2008.
DOI : 10.1117/12.766703

Y. Zhu, P. K. Varshney, and H. Chen, Evaluation of ica based fusion of hyperspectral images for color display, International Conference on Information Fusion, pp.1-7, 2007.