A number of methods have been proposed to separate a color signal into its components: illumination spectral power distribution and surface spectral reflectance. Most of these methods usually use a minimization technique from a single color signal. However, we found that this technique is not effective for real data, because of insufficiency of the constraints. To resolve this problem, we propose a minimization technique that, unlike the existing methods, uses multiple color signals. We present three methods for recovering surface and illumination spectrums which differ in obtaining color signals: first, from two different surface reflectances lit by a single illumination spectral power distribution; second, from identical surface reflectances lit by different illumination spectral power distributions; and third, from a single surface reflectance with two types of reflection components, diffuse and specular, lit by a single illumination spectral power distribution. Practically we applied our method to deal with the color signals of a scene taken by the interference filter, and we separated its illumination spectral power distribution and surface spectral reflectance.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
P.-R. Chang and T.-H. Hsieh, “Constrained nonlinear optimization approaches to color-signal separation,” IEEE Transactions on Image Processing, Vol. 4, No. 1, pp. 81-94, 1995.
N. Chiba, H. Kano, M. Minoh, and M. Yasuda, “Feature-based image mosaicing,” Transactions of IEICE, Vol. J82-D-II, No. 10, pp. 1581-1589, 1999 (in Japanese).
J. Cohen, “Dependency of the spectral reflectance curves of the Munsell color chips,” Psychonomical Science, Vol. 1, pp. 369-370, 1964.
M. D’Zmura and P. Lennie, “Mechanisms of color constancy,” Journal of the Optical Society of America A, Vol. 3, No. 10, pp. 1662-1672, 1986.
M. D’Zmura, “Color constancy: surface color from changing illumination,” Journal of the Optical Society of America A, Vol. 9, No. 3, pp. 490-493, 1992.
G.D. Finlayson, B.V. Funt, and K. Barnard, “Color constancy under varying illumination,” Proceedings of the Fifth International Conference on Computer Vision, pp. 720-725, 1995.
G.D. Finlayson, S.D. Hordley, and P.M. Hubel, “Color by correlation: A simple, unifying framework for color constancy,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 23, No. 11, pp. 1209-1221,2001.
G.D. Finlayson and G. Schaefer, “Solving for colour constancy using a constrained dichromatic reflection model,” International Journal of Computer Vision, Vol. 42, No. 3, pp. 127-144, 2001.
G.D. Finlayson and S.D. Hordley, “Color constancy at a pixel,” Journal of the Optical Society of America A, Vol. 18, No. 2, pp. 253-264, 2001.
Th. Gevers, H.M.G. Stockman, and J. van de Weijer, “Color constancy from hyper-spectral data,” Proceedings of The Eleventh British Machine Vision Conference, 2000.
J. Ho, B.V. Funt, and M.S. Drew, “Separating a color signal into illumination and surface reflectance components: Theory and applications,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 12, No. 10, pp. 966-977, 1990.
D.B. Judd, D.L. MacAdam, and G. Wyszecki, “Spectral distribution of typical daylight as a function of correlated color temperature,” Journal of the Optical Society of America, Vol. 54, No. 8, pp. 1031-1040, 1964.
H.C. Lee, E.J. Breneman, and C.P. Schulte, “Modeling light reflection for computer color vision,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 12, No. 4, pp. 402-409, 1990.
J.A. Marchant and C.M. Onyango, “Spectral invariance under daylight illumination changes,” Journal of the Optical Society of America A, Vol. 19, No. 5, pp. 840-848, 2002.
Y. Nakatani and M. Okutomi, “Image mosaicing using an active camera,” The Journal of the Institute of Image Electronics Engineers of Japan, Vol. 29, No. 5, pp. 462-470, 2000 (in Japanese).
J.P.S. Parkkinen, J. Hallikainen, and T. Jaaskelainen, “Characteristic spectra of Munsell colors,” Journal of the Optical Society of America A, Vol. 6, No. 2, pp. 318-322, 1989.
R. Lenz, P. Meer, M. Hauta-Kasari, “Spectral-based illumination estimation and color correction,” COLOR Research and Application, Vol. 24, No. 2, pp. 98-111, 1999.
Y.Y. Schechner and S.K. Nayar, “Generalized mosaicing: Wide field of view multispectral imaging,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24, No. 10, pp. 1334-1348, 2002.
D. Slater and G. Healey, “What is the spectral dimensionality of illumination functions in outdoor scenes?,” Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 105-110,1998.
R. Szeliski and H.-Y. Shum, “Creating full view panoramic image mosaics and environment maps,” Proceedings of SIGGRAPH 97, pp. 251-258,1997.
R.T. Tan, K. Nishino, and K. Ikeuchi, “Illumination chromaticity estimation using inverse-intensity chromaticity space,” Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 673-680, 2003.
S. Tominaga, “Multichannel vision system for estimating surface and illuminat functions,” Journal of the Optical Society of America A, Vol. 13, No. 11, pp. 2163-2173, 1996.
S. Tominaga, S. Ebisui, and B.A. Wandell, “Scene illuminant classification -brighter is better-,” Journal of the Optical Society of America A, Vol. 18, No. 1, pp. 55-64, 2001.
S. Tominaga, “Surface identification using the dichromatic reflection model,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 13, No. 7, pp. 658-670, 1991.
S. Tominaga and B.A. Wandell, “Standard surface-reflectance model and illuminant estimation,” Journal of the Optical Society of America A, Vol. 6, No. 4, pp. 576-584, 1989.
S. Tominaga and B.A. Wandell, “Natural scene illuminant estimation using the sensor correlation,” Proceedings of The IEEE, Vol. 90, No. 1, pp. 42-56, 2002.
Y. Xiong and K. Turkowski, “Registration, calibration and blending in creating high quality panoramas,” Proceedings of the 4th IEEE Workshop on Applications of Computer Vision, pp. 69-74, 1998.
J.Y. Hardeberg, “On the spectral dimensionality of object colours,” Proceedings of IS&T First European Conference on Colour in Graphics, Image and Vision, pp. 480-485, 2002.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Ikari, A., Kawakami, R., Tan, R.T., Ikeuchi, K. (2008). Separating Illumination and Surface Spectral from Multiple Color Signals. In: Digitally Archiving Cultural Objects. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-75807_15
Download citation
DOI: https://doi.org/10.1007/978-0-387-75807_15
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-75806-0
Online ISBN: 978-0-387-75807-7
eBook Packages: Computer ScienceComputer Science (R0)