A. E. Abdel-hakim and A. A. Farag, CSIFT: A SIFT Descriptor with Color Invariant Characteristics, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2 (CVPR'06), pp.1978-1983, 2006.
DOI : 10.1109/CVPR.2006.95

F. Barnard, V. Cardei, B. Barnard, G. Finlayson, and B. Funt, The coding of sensory messages Current problems in animal behaviour A comparison of computational color constancy algorithms. i : Methodology and experiments with synthesized data Color constancy for scenes with varying illumination A comparison of computational color constancy algorithms Surf : Speeded up robust features, Psychological review, pp.183-331, 1954.

J. Anthony, T. J. Bell, and . Sejnowski, The " independent components " of natural scenes are edge filters, Vision research, vol.379, issue.23, pp.3327-3338, 1997.

S. Belongie, J. Malik, and J. Puzicha, Shape matching and object recognition using shape contexts. Pattern Analysis and Machine Intelligence, IEEE Transactions, vol.24, issue.4, pp.509-522, 2002.

S. Bianco, G. Ciocca, C. Cusano, and R. Schettini, Improving Color Constancy Using Indoor–Outdoor Image Classification, IEEE Transactions on Image Processing, vol.17, issue.12, pp.2381-2392, 2008.
DOI : 10.1109/TIP.2008.2006661

M. Bleier, C. Riess, S. Beigpour, E. Eibenberger, E. Angelopoulou et al., Color constancy and non-uniform illumination: Can existing algorithms work?, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), 2011.
DOI : 10.1109/ICCVW.2011.6130331
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.637.133

M. Bleyer and S. Chambon, Does color really help in dense stereo matching, International Symposium 3D Data Processing, Visualization and Transmission (3DPVT)

A. Bosch, A. Zisserman, and X. Muoz, Scene classification using a hybrid generative/discriminative approach. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.30, issue.4, pp.712-727, 2008.
DOI : 10.1109/tpami.2007.70716

I. Boyadzhiev, K. Bala, S. Paris, and F. Durand, User-guided white balance for mixed lighting conditions, ACM Transactions on Graphics, vol.31, issue.6, pp.1-20010, 2012.
DOI : 10.1145/2366145.2366219
URL : http://dspace.mit.edu/bitstream/1721.1/86952/1/Durand_User-guided%20white.pdf

M. Brown and S. Susstrunk, Multi-spectral SIFT for scene category recognition, CVPR 2011, pp.177-184, 2011.
DOI : 10.1109/CVPR.2011.5995637
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.229.1729

G. Buchsbaum, A spatial processor model for object colour perception, Journal of the Franklin Institute, vol.310, issue.1, pp.1-26, 1980.
DOI : 10.1016/0016-0032(80)90058-7

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

G. J. Burghouts and J. M. Geusebroek, Performance evaluation of local colour invariants, Computer Vision and Image Understanding, vol.113, issue.1, pp.48-62, 2009.
DOI : 10.1016/j.cviu.2008.07.003

M. Calonder, V. Lepetit, C. Strecha, and P. Fua, BRIEF: Binary Robust Independent Elementary Features, Computer Vision?ECCV 2010, pp.778-792, 2010.
DOI : 10.1007/978-3-642-15561-1_56
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.175.2122

A. Chakrabarti, K. Hirakawa, and T. Zickler, Color constancy with spatiospectral statistics. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.34, issue.8, pp.1509-1519, 2012.
DOI : 10.1109/tpami.2011.252
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.231.9154

S. Chambon and A. Crouzil, Colour Correlation-based Matching, International Journal of Robotics and Automation, vol.20, issue.2, pp.78-85, 2005.
DOI : 10.2316/Journal.206.2005.2.206-2783

P. Chang and J. Krumm, Object recognition with color cooccurrence histograms, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149), pp.2498-2504, 1999.
DOI : 10.1109/CVPR.1999.784727

Y. Cheng, Mean shift, mode seeking, and clustering. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.17, issue.8, pp.790-799, 1995.

D. Manh, C. Arnold, and W. Smeulders, Color invariant surf in discriminative object tracking, Trends and Topics in Computer Vision, pp.62-75, 2012.

F. Ciurea and B. Funt, A large image database for color constancy research, 2003.

D. Coffin, Decoding raw digital photos in linux, 2013.

T. Robert, Y. Collins, M. Liu, and . Leordeanu, Online selection of discriminative tracking features. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.27, issue.10, pp.1631-1643, 2005.

A. B. Dahl and H. Aanaes, Effective image database search via dimensionality reduction, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp.1-6, 2008.
DOI : 10.1109/CVPRW.2008.4562957
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.332.8521

J. Delon, A. Desolneux, J. L. Lisani, and A. B. Petro, Automatic color palette, IEEE International Conference on Image Processing 2005, p.706, 2005.
DOI : 10.1109/ICIP.2005.1530153
URL : https://hal.archives-ouvertes.fr/hal-00259056

N. Deriugin, The power spectrum and the correlation function of the television signal, Telecommunications, vol.1, issue.7, pp.1-12, 1956.

B. Joel, G. Derrico, and . Buchsbaum, A computational model of spatiochromatic image coding in early vision, Journal of Visual Communication and Image Representation, vol.2, issue.1, pp.31-38, 1991.

A. Desolneux, L. Moisan, and J. Morel, A grouping principle and four applications, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.25, issue.4, pp.508-513, 2003.
DOI : 10.1109/TPAMI.2003.1190576
URL : https://hal.archives-ouvertes.fr/hal-00170783

A. Desolneux, L. Moisan, and J. M. , From Gestalt Theory to Image Analysis, 2008.
DOI : 10.1007/978-0-387-74378-3
URL : https://hal.archives-ouvertes.fr/hal-00259077

A. Desolneux, L. Moisan, and J. Morel, Edge detection by helmholtz principle, Journal of Mathematical Imaging and Vision, vol.14, issue.3, pp.271-284, 2001.
DOI : 10.1023/A:1011290230196
URL : https://hal.archives-ouvertes.fr/hal-00170793

S. Di and Z. , A note on the gradient of a multi-image, Computer Vision, Graphics, and Image Processing, vol.33, issue.1, pp.116-125, 1986.

M. Ebner, A parallel algorithm for color constancy, Journal of Parallel and Distributed Computing, vol.64, issue.1, pp.79-88, 2004.
DOI : 10.1016/j.jpdc.2003.06.004

M. Ebner, Color constancy, 2007.
DOI : 10.1002/9780470510490

M. Ebner, Estimating the Color of the Illuminant Using Anisotropic Diffusion, Computer Analysis of Images and Patterns, 12th International Conference Proceedings, pp.441-449, 2007.
DOI : 10.1007/978-3-540-74272-2_55

J. David and . Field, Relations between the statistics of natural images and the response properties of cortical cells, JOSA A, vol.4, issue.12, pp.2379-2394, 1987.

G. D. Finlayson and S. D. Hordley, Gamut constrained illuminant estimation, Int. J. Comput. Vision, vol.67, 2006.
DOI : 10.1109/iccv.2003.1238429
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.107.8379

G. Finlayson, S. Hordley, G. Schaefer, and G. Y. Tian, Illuminant and device invariant colour using histogram equalisation, Pattern Recognition, vol.38, issue.2, pp.179-190, 2005.
DOI : 10.1016/j.patcog.2004.04.010
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.455.6623

G. D. Finlayson, M. S. Drew, and B. V. Funt, Color constancy: generalized diagonal transforms suffice, Journal of the Optical Society of America A, vol.11, issue.11, pp.3011-3020, 1994.
DOI : 10.1364/JOSAA.11.003011
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.121.872

D. Graham, . Finlayson, S. Mark, . Drew, V. Brian et al., Spectral sharpening : sensor transformations for improved color constancy, JOSA A, vol.11, issue.5, pp.1553-1563, 1994.

G. D. Finlayson, B. V. Funt, and K. Barnard, Color constancy under varying illumination, Proceedings of IEEE International Conference on Computer Vision, pp.720-725, 1995.
DOI : 10.1109/ICCV.1995.466867

D. Graham, S. D. Finlayson, and . Hordley, Color constancy at a pixel, J. Opt. Soc. Am. A, vol.18, issue.2, pp.253-264, 2001.

D. Graham, . Finlayson, D. Steven, and . Hordley, Color constancy at a pixel, JOSA A, vol.18, issue.2, pp.253-264, 2001.

G. D. Finlayson, S. D. Hordley, and P. M. Hubel, Color by correlation : A simple, unifying framework for color constancy. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.23, issue.11, pp.1209-1221, 2001.

D. Graham, G. Finlayson, and . Schaefer, Solving for colour constancy using a constrained dichromatic reflection model, Int. J. Comput. Vision, vol.42, issue.3, pp.127-144, 2001.

D. Graham, B. Finlayson, . Schiele, L. James, and . Crowley, Comprehensive colour image normalization, Computer Vision?ECCV'98, pp.475-490, 1998.

D. Graham, E. Finlayson, and . Trezzi, Shades of gray and colour constancy, Color Imaging Conference, pp.37-41, 2004.

D. A. Forsyth, A novel algorithm for color constancy, International Journal of Computer Vision, vol.20, issue.10, pp.5-36, 1990.
DOI : 10.1109/TPAMI.1987.4767868

V. Brian, G. D. Funt, and . Finlayson, Color constant color indexing. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.17, issue.5, pp.522-529, 1995.

P. V. Gehler, C. Rother, A. Blake, T. Minka, and T. Sharp, Bayesian color constancy revisited, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2008.
DOI : 10.1109/CVPR.2008.4587765
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.142.9276

T. Geodeme, T. Tuytelaars, . Vanacker, L. Nuttin, and . Van-gool, Omnidirectional sparse visual path following with occlusion-robust feature tracking, OMNIVIS Workshop , ICCV, 2005.

R. Gershon, D. Allan, . Jepson, K. John, and . Tsotsos, From [r, g, b] to surface reflectance : Computing color constant descriptors in images, IJCAI, pp.755-758, 1987.

J. M. Geusebroek, G. J. Burghouts, and A. W. Smeulders, The Amsterdam Library of Object Images, International Journal of Computer Vision, vol.61, issue.1, pp.103-112, 2005.
DOI : 10.1023/B:VISI.0000042993.50813.60

J. M. Geusebroek, T. Gevers, and A. W. Smeulders, The Kubelka-Munk theory for color image invariant properties, European Conference on Colour in Graphics, pp.463-467, 2002.

J. M. Geusebroek, R. Van-den-boomgaard, A. W. Smeulders, and H. Geerts, Color invariance, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.23, issue.12, pp.1338-1350, 2001.
DOI : 10.1109/34.977559

J. Geusebroek, R. Van-den, . Boomgaard, W. Arnold, A. Smeulders et al., Color and Scale: The Spatial Structure of Color Images, Computer Vision-ECCV 2000, pp.331-341, 2000.
DOI : 10.1007/3-540-45054-8_22

T. Gevers and W. Smeulders, Color-based object recognition, Pattern Recognition, vol.32, issue.3, pp.453-464, 1999.
DOI : 10.1016/S0031-3203(98)00036-3
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.21.2506

T. Gevers, W. Arnold, and . Smeulders, Content-based image retrieval by viewpoint-invariant color indexing, Image and Vision Computing, vol.17, issue.7, pp.475-488, 1999.
DOI : 10.1016/S0262-8856(98)00140-1

T. Gevers and H. Stokman, Robust histogram construction from color invariants for object recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.1, pp.113-118, 2003.
DOI : 10.1109/TPAMI.2004.1261083

A. Gijsenij, T. Gevers, and J. Van-de-weijer, Generalized Gamut Mapping using Image Derivative Structures for Color Constancy, International Journal of Computer Vision, vol.16, issue.9, pp.127-139, 2010.
DOI : 10.1017/S0952523806233455
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.175.9416

A. Gijsenij, T. Gevers, and J. Van-de-weijer, Computational Color Constancy: Survey and Experiments, IEEE Transactions on Image Processing, vol.20, issue.9, pp.2475-2489, 2011.
DOI : 10.1109/TIP.2011.2118224
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.221.4932

A. Gijsenij, . Th, M. P. Gevers, and . Lucassen, Perceptual analysis of distance measures for color constancy algorithms, Journal of the Optical Society of America A, vol.26, issue.10, pp.2243-2256, 2009.
DOI : 10.1364/JOSAA.26.002243

A. Gijsenij, . Th, J. Gevers, and . Van-de-weijer, Physics-based edge evaluation for improved color constancy, 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2009.
DOI : 10.1109/CVPR.2009.5206497

A. Gijsenij, R. Lu, and T. Gevers, Color Constancy for Multiple Light Sources, IEEE Transactions on Image Processing, vol.21, issue.2, pp.697-707, 2012.
DOI : 10.1109/TIP.2011.2165219
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.221.4155

A. Gijsenij and T. Gevers, Color Constancy Using Natural Image Statistics and Scene Semantics, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, issue.4, pp.687-698, 2011.
DOI : 10.1109/TPAMI.2010.93

A. Hanbury, Constructing cylindrical coordinate colour spaces, Pattern Recognition Letters, vol.29, issue.4, pp.494-500, 2008.
DOI : 10.1016/j.patrec.2007.11.002
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.140.4289

C. Harris and M. Stephens, A Combined Corner and Edge Detector, Procedings of the Alvey Vision Conference 1988, p.50, 1988.
DOI : 10.5244/C.2.23
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.231.1604

T. Hastie, R. Tibshirani, J. Friedman, . Hastie, R. Friedman et al., The elements of statistical learning, 2009.

J. Hays and A. A. Efros, Scene completion using millions of photographs, Communications of the ACM, vol.51, issue.10, pp.87-94, 2008.
DOI : 10.1145/1400181.1400202

G. Healey and D. Slater, Global color constancy: recognition of objects by use of illumination-invariant properties of color distributions, Journal of the Optical Society of America A, vol.11, issue.11, pp.3003-3010, 1994.
DOI : 10.1364/JOSAA.11.003003

J. Hernández-andrés, R. L. Lee, and J. Romero, Calculating correlated color temperatures across the entire gamut of daylight and skylight chromaticities, Applied Optics, vol.38, issue.27, pp.5703-5709, 1999.
DOI : 10.1364/AO.38.005703

H. Hirschmuller and D. Scharstein, Evaluation of stereo matching costs on images with radiometric differences. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.31, issue.9, pp.1582-1599, 2009.

E. Hsu, T. Mertens, S. Paris, S. Avidan, and F. Durand, Light mixture estimation for spatially varying white balance, ACM Trans. Graph, vol.2770, issue.3, pp.1-70, 2008.
DOI : 10.1145/1399504.1360669
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.153.5497

J. Huang and D. Mumford, Statistics of natural images and models, Computer Vision and Pattern Recognition, 1999.

Y. Imai, Y. Kato, H. Kadoi, T. Horiuchi, and S. Tominaga, Estimation of Multiple Illuminants Based on Specular Highlight Detection, Proceedings of the Third international conference on Computational color imaging, pp.85-98, 2011.
DOI : 10.1007/978-3-642-20404-3_7

H. Jégou, M. Douze, C. Schmid, and P. Pérez, Aggregating local descriptors into a compact image representation, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.3304-3311, 2010.
DOI : 10.1109/CVPR.2010.5540039

J. Jiang, D. Liu, J. Gu, and S. Süsstrunk, What is the space of spectral sensitivity functions for digital color cameras ? In WACV, pp.168-179, 2013.

D. B. Judd, D. L. Macadam, G. Wyszecki, H. W. Budde, H. R. Condit et al., Spectral Distribution of Typical Daylight as a Function of Correlated Color Temperature, Journal of the Optical Society of America, vol.54, issue.8, pp.541031-1036, 1964.
DOI : 10.1364/JOSA.54.001031

D. Brewster and J. , Color in business, science, and industry, 1952.

B. Kang, O. Moon, C. Hong, H. Lee, B. Cho et al., Design of advanced color -temperature control system for hdtv applications, Journal of the Korean Physical Society, vol.41, issue.6, pp.865-871, 2002.

R. Kawakami, R. T. Tan, and K. Ikeuchi, A robust framework to estimate surface color from changing illumination, Asian Conference on Computer Vision (ACCV2004), 2004.

Y. Ke and R. Sukthankar, Pca-sift : a more distinctive representation for local image descriptors, Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition, CVPR'04, pp.506-513, 2004.

M. James, . Kraft, H. David, and . Brainard, Mechanisms of color constancy under nearly natural viewing, Proceedings of the National Academy of Sciences, pp.307-312, 1999.

H. Kwon, S. Lee, T. Bae, and K. Sohng, Compensation of de-saturation effect in HDR imaging using a real scene adaptation model, Journal of Visual Communication and Image Representation, vol.24, issue.6, pp.678-685, 2013.
DOI : 10.1016/j.jvcir.2012.03.001

E. H. Land and J. J. Mccann, Lightness and Retinex Theory, Journal of the Optical Society of America, vol.61, issue.1, pp.1-11, 1971.
DOI : 10.1364/JOSA.61.000001
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.157.4262

B. Ann, D. Lee, J. Mumford, and . Huang, Occlusion models for natural images : A statistical study of a scale-invariant dead leaves model, International Journal of Computer Vision, vol.41, issue.12, pp.35-59, 2001.

R. Lenz, L. V. Tran, and P. Meer, Moment based normalization of color images, 1999 IEEE Third Workshop on Multimedia Signal Processing (Cat. No.99TH8451), pp.103-108, 1999.
DOI : 10.1109/MMSP.1999.793805

B. Li, D. Xu, W. Xiong, and S. Feng, Color constancy using achromatic surface, Color Research & Application, vol.23, issue.4, pp.304-312, 2010.
DOI : 10.1016/0016-0032(80)90058-7

T. Lindeberg, Scale-space theory: a basic tool for analyzing structures at different scales, Journal of Applied Statistics, vol.21, issue.1, pp.225-270, 1994.
DOI : 10.1080/757582976

G. David and . Lowe, Distinctive image features from scale-invariant keypoints, International Journal of Computer Vision, vol.60, pp.91-110, 2004.

L. David and . Macadam, Visual sensitivities to color differences in daylight, JOSA, vol.32, issue.5, pp.247-273, 1942.

M. Donald and . Mackay, Towards an information-flow model of human behaviour, British Journal of Psychology, vol.47, issue.1, pp.30-43, 1956.

G. Stéphane and . Mallat, A theory for multiresolution signal decomposition : the wavelet representation. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.11, issue.7, pp.674-693, 1989.

T. Laurence and . Maloney, Evaluation of linear models of surface spectral reflectance with small numbers of parameters, JOSA A, vol.3, issue.10, pp.1673-1683, 1986.

J. Matas, O. Chum, M. Urban, and T. Pajdla, Robust wide-baseline stereo from maximally stable extremal regions, Image and Vision Computing, vol.22, issue.10, pp.761-767, 2004.
DOI : 10.1016/j.imavis.2004.02.006
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.671.8241

J. Matas, D. Koubaroulis, and J. Kittler, Colour Image Retrieval and Object Recognition Using the Multimodal Neighbourhood Signature, Proceedings of the 6th European Conference on Computer Vision-Part I, ECCV '00, pp.48-64, 2000.
DOI : 10.1007/3-540-45054-8_4

J. Baptiste-mazin, Y. Delon, and . Gousseau, Illuminant estimation from projections on the planckian locus, ECCV Workshops, pp.370-379, 2012.

J. Baptiste-mazin, Y. Delon, and . Gousseau, Estimation automatique d'illuminant multiples, proceedings of GRETSI 2013, 2013.

K. Mikolajczyk and C. Schmid, Indexing based on scale invariant interest points, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, pp.525-531, 2001.
DOI : 10.1109/ICCV.2001.937561
URL : https://hal.archives-ouvertes.fr/inria-00548276

K. Mikolajczyk and C. Schmid, An Affine Invariant Interest Point Detector, Computer Vision?ECCV 2002, pp.128-142, 2002.
DOI : 10.1007/3-540-47969-4_9
URL : https://hal.archives-ouvertes.fr/inria-00548252

K. Mikolajczyk and C. Schmid, A performance evaluation of local descriptors, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.27, issue.10, pp.1615-1630, 2005.
DOI : 10.1109/TPAMI.2005.188
URL : https://hal.archives-ouvertes.fr/inria-00548227

K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, J. Matas et al., A Comparison of Affine Region Detectors, International Journal of Computer Vision, vol.65, issue.1-2, pp.43-72, 2005.
DOI : 10.1007/s11263-005-3848-x
URL : https://hal.archives-ouvertes.fr/inria-00548528

F. Mindru, T. Tuytelaars, L. Van-gool, and T. Moons, Moment invariants for recognition under changing viewpoint and illumination, Computer Vision and Image Understanding, vol.94, issue.1-3, pp.3-27, 2004.
DOI : 10.1016/j.cviu.2003.10.011
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.5.3379

L. Moisan, P. Moulon, and P. Monasse, Automatic Homographic Registration of a Pair of Images, with A Contrario Elimination of Outliers, Image Processing On Line, vol.2, 2012.
DOI : 10.5201/ipol.2012.mmm-oh
URL : https://hal.archives-ouvertes.fr/hal-00711852

P. Moreels and P. Perona, Evaluation of Features Detectors and Descriptors based on 3D Objects, International Journal of Computer Vision, vol.59, issue.1, pp.263-284, 2007.
DOI : 10.1007/s11263-006-9967-1

J. Morel and G. Yu, ASIFT: A New Framework for Fully Affine Invariant Image Comparison, SIAM Journal on Imaging Sciences, vol.2, issue.2, pp.438-469, 2009.
DOI : 10.1137/080732730

N. Moroney, D. Mark, . Fairchild, W. Robert, C. Hunt et al., The ciecam02 color appearance model, Color and Imaging Conference, pp.23-27, 2002.

K. Mühlmann, D. Maier, J. Hesser, and R. Männer, Calculating dense disparity maps from color stereo images, an efficient implementation, Proceedings IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV 2001), pp.79-88, 2002.
DOI : 10.1109/SMBV.2001.988760

S. Kumar, N. , and C. Murthy, Distinct multicolored region descriptors for object recognition . Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.29, issue.7, pp.1291-1296, 2007.

K. Shree, . Nayar, M. Ruud, and . Bolle, Reflectance based object recognition, International Journal of Computer Vision, vol.17, issue.3, pp.219-240, 1996.

R. Nevatia, A color edge detector and its use in scene segmentation, IEEE Transactions on systems, Man, and Cybernetics, vol.7, issue.11, pp.820-826, 1977.

R. Ohlaxnder, K. Price, and . Reddy, Picture segmentation using a recursive region splitting method, Computer Graphics and Image Processing, vol.8, issue.3, pp.313-333, 1978.
DOI : 10.1016/0146-664X(78)90060-6

Y. Ohta, T. Kanade, and T. Sakai, Color information for region segmentation . Computer graphics and image processing, pp.222-241, 1980.
DOI : 10.1016/0146-664x(80)90047-7

T. Ojala, M. Pietikainen, and T. Maenpaa, Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.24, issue.7, pp.971-987, 2002.
DOI : 10.1109/tpami.2002.1017623
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.157.1576

B. Olshausen and D. Field, Emergence of simple-cell receptive field properties by learning a sparse code for natural images, Nature, vol.381, issue.6583, pp.607-609, 1996.
DOI : 10.1038/381607a0

A. Bruno and . Olshausen, Emergence of simple-cell receptive field properties by learning a sparse code for natural images, Nature, issue.6583, pp.381607-609, 1996.

P. Pérez, C. Hue, J. Vermaak, and M. Gangnet, Color-Based Probabilistic Tracking, Computer vision?ECCV 2002, pp.661-675, 2002.
DOI : 10.1007/3-540-47969-4_44

G. Irwin and . Priest, A proposed scale for use in specifying the chromaticity of incandescent illuminants and various phases of daylight, J. Opt. Soc. Am, vol.23, issue.2, pp.41-45, 1933.

P. Quelhas and J. Odobez, A Color and Gradient Local Descriptor Fusion Scheme For Object Recognition, EPFL, 2003.

J. Rabin, J. Delon, and Y. Gousseau, Circular earth mover's distance for the comparison of local features, Proceedings of ICPR 2008, 2008.

J. Rabin, J. Delon, and Y. Gousseau, A Statistical Approach to the Matching of Local Features, SIAM Journal on Imaging Sciences, vol.2, issue.3, pp.931-958, 2009.
DOI : 10.1137/090751359
URL : https://hal.archives-ouvertes.fr/hal-00168285

J. Rissanen, A universal prior for integers and estimation by minimum description length. The Annals of statistics, pp.416-431, 1983.

C. Rosenberg, M. Hebert, and S. Thrun, Color constancy using kldivergence, Computer Vision Proceedings. Eighth IEEE International Conference on, pp.239-246, 2001.
DOI : 10.1109/iccv.2001.937524
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.2.2465

Y. Rubner, C. Tomasi, and L. J. Guibas, A metric for distributions with applications to image databases, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271), pp.59-66, 1998.
DOI : 10.1109/ICCV.1998.710701

Y. Rubner, C. Tomasi, and L. J. Guibas, The earth mover's distance as a metric for image retrieval, International Journal of Computer Vision, vol.40, issue.2, pp.99-121, 2000.
DOI : 10.1023/A:1026543900054

L. Daniel and . Ruderman, The statistics of natural images Network : computation in neural systems, pp.517-548, 1994.

L. Daniel, . Ruderman, W. Thomas, C. Cronin, and . Chiao, Statistics of cone responses to natural images : Implications for visual coding, JOSA A, vol.15, issue.8, pp.2036-2045, 1998.

G. Sapiro, Color and illuminant voting, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.21, issue.11, pp.1210-1215, 1999.
DOI : 10.1109/34.809114

A. Steven and . Shafer, Using color to separate reflection components, Color Research & Application, vol.10, issue.4, pp.210-218, 1985.

F. Shahbaz-khan, J. Van-de-weijer, and M. Vanrell, Top-down color attention for object recognition, 2009 IEEE 12th International Conference on Computer Vision, pp.979-986, 2009.
DOI : 10.1109/ICCV.2009.5459362

L. Shi and B. , Re-processed version of the gehler color constancy dataset of 568 images, 2010.

P. Eero, . Simoncelli, H. Edward, and . Adelson, Noise removal via bayesian wavelet coring, Image Processing Proceedings., International Conference on, pp.379-382, 1996.

A. Ray and S. , Color gamut transform pairs, SIGGRAPH Comput. Graph, vol.12, pp.12-19, 1978.

H. Stern and B. Efros, Adaptive color space switching for tracking under varying illumination, Image and Vision Computing, vol.23, issue.3, pp.353-364, 2005.
DOI : 10.1016/j.imavis.2004.09.005

A. Markus and . Stricker, Color and geometry as cues for indexing, 1992.

J. Michael, D. H. Swain, and . Ballard, Color indexing, International Journal of Computer Vision, vol.7, pp.11-32, 1991.

E. Tola, V. Lepetit, and P. Fua, Daisy : An efficient dense descriptor applied to widebaseline stereo. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.32, issue.5, pp.815-830, 2010.
DOI : 10.1109/tpami.2009.77
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.168.5084

A. Torralba, R. Fergus, T. William, and . Freeman, 80 million tiny images : A large data set for nonparametric object and scene recognition. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.30, issue.11, pp.1958-1970, 2008.

K. E. Van-de-sande, T. Gevers, and C. G. Snoek, Evaluating Color Descriptors for Object and Scene Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.9, pp.1582-1596, 2010.
DOI : 10.1109/TPAMI.2009.154

J. Van-de-weijer, T. Gevers, and A. Gijsenij, Edge-Based Color Constancy, IEEE Transactions on Image Processing, vol.16, issue.9, pp.2207-2214, 2007.
DOI : 10.1109/TIP.2007.901808
URL : https://hal.archives-ouvertes.fr/inria-00548686

J. Van-de-weijer, T. Gevers, and J. Geusebroek, Edge and corner detection by photometric quasi-invariants. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.27, issue.4, pp.625-630, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00548526

J. Van-de-weijer, T. Gevers, W. Arnold, and . Smeulders, Robust photometric invariant features from the color tensor, IEEE Transactions on Image Processing, vol.15, issue.1, pp.118-127, 2006.
DOI : 10.1109/TIP.2005.860343
URL : https://hal.archives-ouvertes.fr/inria-00548599

J. Van, D. Weijer, and C. Schmid, Coloring local feature extraction, European Conference on Computer Vision, pp.334-348, 2006.
URL : https://hal.archives-ouvertes.fr/inria-00548576

J. Van-de-weijer, C. Schmid, and J. Verbeek, Using High-Level Visual Information for Color Constancy, 2007 IEEE 11th International Conference on Computer Vision, pp.1-8, 2007.
DOI : 10.1109/ICCV.2007.4409109
URL : https://hal.archives-ouvertes.fr/inria-00321125

J. Vazquez-corral, M. Vanrell, R. Baldrich, and F. Tous, Color Constancy by Category Correlation, IEEE Transactions on Image Processing, vol.21, issue.4, pp.1997-2007, 2012.
DOI : 10.1109/TIP.2011.2171353

J. Kries, Influence of Adaptation on the Effects Produced by Luminous Stimuli, 1970.

T. Wachtler, T. Lee, and T. J. Sejnowski, Chromatic structure of natural scenes, Journal of the Optical Society of America A, vol.18, issue.1, pp.65-77, 2001.
DOI : 10.1364/JOSAA.18.000065

J. Wang and Y. Yagi, Integrating Color and Shape-Texture Features for Adaptive Real-Time Object Tracking, IEEE Transactions on Image Processing, vol.17, issue.2, pp.235-240, 2008.
DOI : 10.1109/TIP.2007.914150

P. Weinzaepfel, H. Jégou, and P. Pérez, Reconstructing an image from its local descriptors, CVPR 2011, pp.337-344, 2011.
DOI : 10.1109/CVPR.2011.5995616
URL : https://hal.archives-ouvertes.fr/inria-00566718

D. Zhang, W. Wang, W. Gao, and S. Jiang, An Effective Local Invariant Descriptor Combining Luminance and Color Information, Multimedia and Expo, 2007 IEEE International Conference on, pp.1507-1510, 2007.
DOI : 10.1109/ICME.2007.4284948

C. Zhu, C. Bichot, and L. Chen, Multi-scale Color Local Binary Patterns for Visual Object Classes Recognition, 2010 20th International Conference on Pattern Recognition, pp.3065-3068, 2010.
DOI : 10.1109/ICPR.2010.751
URL : https://hal.archives-ouvertes.fr/hal-01381600

C. Song, D. Zhu, and . Mumford, Prior learning and gibbs reaction-diffusion. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.19, issue.11, pp.1236-1250, 1997.