Abstract
We work on a Bayesian approach to the estimation of the specular component of a color image, based on the Dichromatic Reflection Model (DRM). The separation of diffuse and specular components is important for color image segmentation, to allow the segmentation algorithms to work on the best estimation of the reflectance of the scene. In this work we postulate a prior and likelihood energies that model the reflectance estimation process. Minimization of the posterior energy gives the desired reflectance estimation. The approach includes the illumination color normalization and the computation of a specular free image to test the pure diffuse reflection hypothesis.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Ma, W.-C., Hawkins, T., Peers, P., Chabert, C.-F., Weiss, M., Debevec, P.: Rapid acquisition of specular and diffuse normal maps from polarized spherical gradient illumination. In: Eurographics Symposium on Rendering 2007 (2007)
Fu, Z., Tan, R.T., Caelli, T.: Specular free spectral imaging using orthogonal subspace projection. In: 18th International Conference on Pattern Recognition, 2006. ICPR 2006, vol. 1, pp. 812–815 (2006)
Winkler, G.: Image analysis, random fields and dynamic Monte Carlo methods. Springer, Heidelberg (1995)
Hara, K., Nishino, K., Ikeuchi, K.: Light source position and reflectance estimation from a single view without the distant illumination assumption. IEEE Trans. Pattern Anal. Mach. Intell. 27(4), 493–505 (2005)
Jensen, H.W., Marschner, S.R., Levoy, M., Hanrahan, P.: A practical model for subsurface light transport. In: Proceedings of the 28th annual conference on Computer graphics and interactive techniques, pp. 511–518. ACM Press, New York (2001)
Choi, Y.-J., Yoon, K.-J., Kweon, I.S.: Illuminant chromaticity estimation using dichromatic slope and dichromatic line space. In: Korea-Japan Joint Workshop on Frontiers of Computer Vision, pp. 219–224. FCV (2005)
Phong, B.T.: Illumination for computer-generated images. PhD thesis, The University of Utah (1973)
Shafer, S.A.: Using color to separate reflection components. Color Research and Aplications 10, 43–51 (1984)
Tan, R.T., Nishino, K., Ikeuchi, K.: Color constancy through inverse-intensity chromaticity space. J. Opt. Soc. Am. A Opt. Image Sci. Vis. 21(3), 321–334 (2004)
Tan, R.T., Nishino, K., Ikeuchi, K.: Separating reflection components based on chromaticity and noise analysis. IEEE Trans. Pattern Anal. Mach. Intell. 26(10), 1373–1379 (2004)
Tan, R.T., Ikeuchi, K.: Separating reflection components of textured surfaces using a single image. In: Proceedings of Ninth IEEE International Conference on Computer Vision, 2003, October 13-16, 2003, vol. 2, pp. 870–877 (2003)
Tan, R.T., Ikeuchi, K.: Reflection components decomposition of textured surfaces using linear basis functions. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005. CVPR 2005, June 20-25, 2005, vol. 1, pp. 125–131 (2005)
Tan, R.T., Ikeuchi, K.: Separating reflection components of textured surfaces using a single image. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(2), 178–193 (2005)
Toro, J.: Dichromatic illumination estimation without pre-segmentation. Pattern Recogn. Lett. 29, 871–877 (2008)
Toro, J., Funt, B.: A multilinear constraint on dichromatic planes for illumination estimation. IEEE transactions on image processing: a publication of the IEEE Signal Processing Society 16, 92–97 (2007) PMID: 17283768
Ward, G.J.: Measuring and modeling anisotropic reflection. SIGGRAPH Comput. Graph. 26, 265–272 (1992)
Yoon, K.-J., Choi, Y., Kweon, I.S.: Fast separation of reflection components using a specularity-invariant image representation. In: 2006 IEEE International Conference on Image Processing, October 8-11, 2006, pp. 973–976 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Moreno, R., Graña, M., d’Anjou, A., Hernandez, C. (2009). Bayesian Reflectance Component Separation. In: Velásquez, J.D., Ríos, S.A., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2009. Lecture Notes in Computer Science(), vol 5712. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04592-9_105
Download citation
DOI: https://doi.org/10.1007/978-3-642-04592-9_105
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04591-2
Online ISBN: 978-3-642-04592-9
eBook Packages: Computer ScienceComputer Science (R0)