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J. Orava, J. Parkkinen, M. Hauta-kasari, P. Hyvönen, and A. Wright, Temporal clustering of minced meat by RGB and spectral imaging, Journal of Food Engineering, vol.112, issue.1, pp.112-116, 2012.
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A. Messano and M. Singh, Technology for multispectral scanning, detection and imaging for medical diagnosis, 2016 10th International Symposium on Medical Information and Communication Technology (ISMICT), pp.1-3, 2016.
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J. R. Mansfield, Multispectral imaging: A review of its technical aspects and applications in anatomic pathology, Veterinary Pathology, vol.51, issue.1, p.24129898, 2014.

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H. A. Khan, J. Thomas, and J. Y. Hardeberg, Towards highlight based illuminant estimation in multispectral images, Proceedings of International Conference on Image and Signal Processing, pp.517-525, 2018.
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M. Ebner, Color constancy based on local space average color, Machine Vision and Applications, vol.20, pp.283-301, 2009.
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J. Huo, Y. Chang, J. Wang, and X. Wei, Robust automatic white balance algorithm using gray color points in images, IEEE Transactions on Consumer Electronics, vol.52, pp.541-546, 2006.

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

J. Van-de-weijer and T. Gevers, Color constancy based on the grey-edge hypothesis, IEEE International Conference on Image Processing, vol.2, pp.722-727, 2005.
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J. Van-de-weijer, T. Gevers, and A. Gijsenij, Edge-based color constancy, IEEE Transactions on Image Processing, vol.16, pp.2207-2214, 2007.
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T. Celik and T. Tjahjadi, Adaptive colour constancy algorithm using discrete wavelet transform, Computer Vision and Image Understanding, vol.116, issue.4, pp.561-571, 2012.
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A. Gijsenij and T. Gevers, Color constancy using natural image statistics and scene semantics, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, pp.687-698, 2011.
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T. M. Lehmann and C. Palm, Color line search for illuminant estimation in real-world scenes, J. Opt. Soc. Am. A, vol.18, pp.2679-2691, 2001.
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Y. Uchimi, T. Jinno, and S. Kuriyama, Estimation of multiple illuminant colors using color lines of single image, Int. Conf. on Adv. Informatics, Concepts, Theory, and Applications, pp.1-6, 2017.

J. Kim, Y. Seo, and Y. Ha, Estimation of illuminant chromaticity from single color image using perceived illumination and highlight, Journal of Imaging Science and Technology, vol.45, issue.3, pp.274-282, 2001.

O. Kwon, Y. Cho, Y. Kim, and Y. Ha, Illumination estimation based on valid pixel selection in highlight region, IEEE International Conf. on Image Processing, 2004.

E. Lakehal and D. Ziou, Computational color constancy from maximal projections mean assumption, Multimedia Tools and Applications, 2017.
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G. D. Finlayson and G. Schaefer, Solving for colour constancy using a constrained dichromatic reflection model, International Journal of Computer Vision, vol.42, pp.127-144, 2001.

G. Schaefer, Robust dichromatic colour constancy, Image Analysis and Recognition, pp.257-264, 2004.
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Y. Li and H. Lee, Auto white balance by surface reflection decomposition, J. Opt. Soc. Am. A, vol.34, pp.1800-1809, 2017.
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B. Mazin, J. Delon, and Y. Gousseau, Illuminant estimation from projections on the planckian locus, European Conf. on Computer Vision, pp.370-379, 2012.
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R. T. Tan, K. Nishino, and K. Ikeuchi, Color constancy through inverseintensity chromaticity space, J. Opt. Soc. Am. A, vol.21, pp.321-334, 2004.
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C. Riess, E. Eibenberger, and E. Angelopoulou, Illuminant color estimation for real-world mixed-illuminant scenes, International Conference on Computer Vision, pp.782-789, 2011.
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H. A. Khan, J. Thomas, and J. Y. Hardeberg, Analytical survey of highlight detection in color and spectral images, Computational Color Imaging Workshop, pp.197-208, 2017.
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L. Shi and B. Funt, Dichromatic illumination estimation via Hough transforms in 3D, Conf. on Color in Graphics, Imaging, & Vision, pp.259-262, 2008.

V. C. Cardei, B. Funt, and K. Barnard, Estimating the scene illumination chromaticity by using a neural network, J. Opt. Soc. Am. A, vol.19, pp.2374-2386, 2002.

H. R. Joze and M. S. Drew, Improved machine learning for image category recognition by local color constancy, IEEE International Conference on Image Processing, pp.3881-3884, 2010.

J. T. Barron, Convolutional color constancy, IEEE International Conference on Computer Vision, pp.379-387, 2015.

V. Agarwal, A. V. Gribok, and M. A. Abidi, Machine learning approach to color constancy, Neural Networks, vol.20, issue.5, pp.559-563, 2007.

N. Wang, D. Xu, and B. Li, Edge-Based Color Constancy via Support Vector Regression, IEICE Transactions on Information and Systems, vol.92, pp.2279-2282, 2009.

Z. Lou, T. Gevers, N. Hu, and M. Lucassen, Color constancy by deep learning, British Machine Vision Conference, 2015.

W. Shi, C. C. Loy, and X. Tang, Deep specialized network for illuminant estimation, European Conference on Computer Vision, pp.371-387, 2016.

S. W. Oh and S. J. Kim, Approaching the computational color constancy as a classification problem through deep learning, Pattern Recognition, vol.61, pp.405-416, 2017.

S. Bianco, C. Cusano, and R. Schettini, Color constancy using CNNs, IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.81-89, 2015.

F. Imai and R. Berns, Spectral estimation using trichromatic digital cameras, International Symposium on Multispectral Imaging and Color Reproduction for Digital Archives, pp.42-49, 1999.

D. Connah, S. Westland, and M. G. Thomson, Recovering spectral information using digital camera systems, Coloration Technology, vol.117, issue.6, pp.309-312, 2001.

R. Shrestha and J. Y. Hardeberg, Spectrogenic imaging: A novel approach to multispectral imaging in an uncontrolled environment, Opt. Express, vol.22, pp.9123-9133, 2014.

J. Y. Hardeberg and R. Shrestha, Multispectral colour imaging: Time to move out of the lab?, Mid-term meeting of the International Colour Association (AIC), pp.28-32, 2015.

G. D. Finlayson and E. Trezzi, Shades of gray and colour constancy, 12 th Color Imaging Conference, pp.37-41, 2004.

J. Van-de-weijer, T. Gevers, and A. Gijsenij, Edge-based color constancy, IEEE Transactions on Image Processing, vol.16, pp.2207-2214, 2007.
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J. Thomas, Illuminant estimation from uncalibrated multispectral images, Colour and Visual Computing Symposium (CVCS), (Gjøvik, Norway), vol.20, pp.2475-2489, 2011.

K. Barnard, V. Cardei, and B. Funt, A comparison of computational color constancy algorithms -Part I: Methodology and experiments with synthesized data, IEEE Transactions on Image Processing, vol.11, pp.972-984, 2002.

S. D. Hordley, Scene illuminant estimation: Past, present, and future, Color Research & Application, vol.31, issue.4, pp.303-314, 2006.

F. H. Imai and R. S. Berns, Spectral estimation using trichromatic digital cameras, Proceedings of the International Symposium on Multispectral Imaging and Color Reproduction for Digital Archives, pp.1-8, 1999.

J. Y. Hardeberg, Acquisition and Reproduction of Color Images: Colorimetric and Multispectral Approaches, 2001.

D. Connah, S. Westland, and M. G. Thomson, Recovering spectral information using digital camera systems, Coloration Technology, vol.117, pp.309-312, 2001.
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E. M. Valero, J. L. Nieves, S. M. Nascimento, K. Amano, and D. H. Foster, Recovering spectral data from natural scenes with an RGB digital camera and colored filters, Color Research & Application, vol.32, issue.5, pp.352-360, 2007.
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J. Y. Hardeberg and R. Shrestha, Multispectral colour imaging: Time to move out of the lab?, Mid-term meeting of the International Colour Association (AIC), pp.28-32, 2015.

L. T. Maloney, Evaluation of linear models of surface spectral reflectance with small numbers of parameters, J. Opt. Soc. Am. A, vol.3, pp.1673-1683, 1986.

L. T. Maloney and B. A. Wandell, Color constancy: a method for recovering surface spectral reflectance, J. Opt. Soc. Am. A, vol.3, pp.29-33, 1986.
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J. Van-de-weijer, T. Gevers, and A. Gijsenij, Edge-based color constancy, IEEE Transactions on Image Processing, vol.16, pp.2207-2214, 2007.
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H. Y. Chong, S. J. Gortler, and T. Zickler, The von Kries hypothesis and a basis for color constancy, Proceedings of the IEEE International Conference on Computer Vision, pp.1-8, 2007.
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G. D. Finlayson, J. Vazquez-corral, S. Süsstrunk, and M. Vanrell, Spectral sharpening by spherical sampling, J. Opt. Soc. Am. A, vol.29, issue.7, p.1199, 2012.
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M. Abdellatif, Physics-based spectral sharpening through filter-chart calibration, Color Research & Application, vol.40, pp.564-576, 2015.
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K. Barnard, L. Martin, B. Funt, and A. Coath, A data set for color research, Color Research & Application, vol.27, issue.3, pp.147-151, 2002.

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R. Shrestha and J. Y. Hardeberg, Evaluation and comparison of multispectral imaging systems, Color and Imaging Conference, pp.107-112, 2014.

P. J. Lapray, X. Wang, J. B. Thomas, and P. Gouton, Multispectral filter arrays: Recent advances and practical implementation, Sensors, vol.14, pp.21626-21659, 2014.
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X. Wang, J. Thomas, J. Y. Hardeberg, and P. Gouton, Multispectral imaging: narrow or wide band filters?, Journal of the International Colour Association, vol.12, pp.44-51, 2014.
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P. J. Lapray, J. B. Thomas, P. Gouton, and Y. Ruichek, Energy balance in spectral filter array camera design, Journal of the European Optical Society, vol.13, p.1, 2017.
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J. B. Thomas, P. J. Lapray, P. Gouton, and C. Clerc, Spectral characterization of a prototype SFA camera for joint visible and NIR acquisition, Sensors, vol.16, p.993, 2016.
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J. Conde, H. Haneishi, M. Yamaguchi, N. Ohyama, and J. Baez, Spectral reflectance estimation of ancient Mexican codices, multispectral images approach, Revista Mexicana de Fisica, vol.50, issue.5, pp.484-489, 2004.

D. Connah, J. Y. Hardeberg, and S. Westland, Comparison of linear spectral reconstruction methods for multispectral imaging, International Conference on Image Processing, vol.3, pp.1497-1500, 2004.

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R. Shrestha and J. Y. Hardeberg, Spectrogenic imaging: A novel approach to multispectral imaging in an uncontrolled environment, Opt. Express, vol.22, pp.9123-9133, 2014.

J. Y. Hardeberg and R. Shrestha, Multispectral colour imaging: Time to move out of the lab?, Mid-term meeting of the International Colour Association (AIC), pp.28-32, 2015.

J. Thomas, Illuminant estimation from uncalibrated multispectral images, Colour and Visual Computing Symposium (CVCS), (Gjøvik, Norway), pp.1-6, 2015.

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M. J. Swain and D. H. Ballard, Color indexing, International Journal of Computer Vision, vol.7, issue.1, pp.11-32, 1991.

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

T. Gevers and A. W. Smeulders, Color-based object recognition, Pattern Recognition, vol.32, issue.3, pp.453-464, 1999.

S. D. Hordley, Scene illuminant estimation: Past, present, and future, Color Research and Application, vol.31, issue.4, pp.303-314, 2006.

L. T. Maloney and B. A. Wandell, Color constancy: a method for recovering surface spectral reflectance, J. Opt. Soc. Am. A, vol.3, pp.29-33, 1986.

D. Cheng, B. Price, S. Cohen, and M. S. Brown, Effective learning-based illuminant estimation using simple features, IEEE Conference on Computer Vision and Pattern Recognition, pp.1000-1008, 2015.

M. D'zmura and P. Lennie, Mechanisms of color constancy, J. Opt. Soc. Am. A, vol.3, pp.1662-1672, 1986.

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E. H. Land and J. J. Mccann, Lightness and retinex theory, J. Opt. Soc. Am, vol.61, pp.1-11, 1971.

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

, Article B: Illuminant estimation in multispectral imaging

J. Van-de-weijer, T. Gevers, and A. Gijsenij, Edge-based color constancy, IEEE Transactions on Image Processing, vol.16, pp.2207-2214, 2007.
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T. Celik and T. Tjahjadi, Adaptive colour constancy algorithm using discrete wavelet transform, Computer Vision and Image Understanding, vol.116, issue.4, pp.561-571, 2012.

A. Chakrabarti, K. Hirakawa, and T. Zickler, Color constancy with spatiospectral statistics, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.34, pp.1509-1519, 2012.

M. Rezagholizadeh and J. Clark, Edge-based and efficient chromaticity spatio-spectral models for color constancy, International Conference on Computer and Robot Vision, pp.188-195, 2013.

A. Gijsenij and T. Gevers, Color constancy using natural image statistics and scene semantics, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, pp.687-698, 2011.

D. Forsyth, A novel algorithm for color constancy, International Journal of Computer Vision, vol.5, issue.1, pp.5-35, 1990.

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.86, issue.2, pp.127-139, 2010.

J. Huo, Y. Chang, J. Wang, and X. Wei, Robust automatic white balance algorithm using gray color points in images, IEEE Transactions on Consumer Electronics, vol.52, pp.541-546, 2006.

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