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Separating Reflection Components of Textured Surfaces Using a Single Image
February 2005 (vol. 27 no. 2)
pp. 178-193
ASCII Text
x 
 
Robby T. Tan, Katsushi Ikeuchi, "Separating Reflection Components of Textured Surfaces Using a Single Image," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 2, pp. 178-193, February, 2005.
 
 
BibTex
x
 
@article{ 10.1109/TPAMI.2005.36,
author = {Robby T. Tan and Katsushi Ikeuchi},
title = {Separating Reflection Components of Textured Surfaces Using a Single Image},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {27},
number = {2},
issn = {0162-8828},
year = {2005},
pages = {178-193},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2005.36},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - Separating Reflection Components of Textured Surfaces Using a Single Image
IS - 2
SN - 0162-8828
SP178
EP193
EPD - 178-193
A1 - Robby T. Tan,
A1 - Katsushi Ikeuchi,
PY - 2005
KW - Reflection components separation
KW - specular reflection
KW - diffuse reflection
KW - dichromatic reflection model
KW - chromaticity
KW - specular-to-diffuse mechanism
KW - specular-free image.
VL - 27
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 
In inhomogeneous objects, highlights are linear combinations of diffuse and specular reflection components. A number of methods have been proposed to separate or decompose these two components. To our knowledge, all methods that use a single input image require explicit color segmentation to deal with multicolored surfaces. Unfortunately, for complex textured images, current color segmentation algorithms are still problematic to segment correctly. Consequently, a method without explicit color segmentation becomes indispensable and this paper presents such a method. The method is based solely on colors, particularly chromaticity, without requiring any geometrical information. One of the basic ideas is to iteratively compare the intensity logarithmic differentiation of an input image and its specular-free image. A specular-free image is an image that has exactly the same geometrical profile as the diffuse component of the input image and that can be generated by shifting each pixel's intensity and maximum chromaticity nonlinearly. Unlike existing methods using a single image, all processes in the proposed method are done locally, involving a maximum of only two neighboring pixels. This local operation is useful for handling textured objects with complex multicolored scenes. Evaluations by comparison with the results of polarizing filters demonstrate the effectiveness of the proposed method.

[1] R. Bajscy, S.W. Lee, and A. Leonardis, “Detection of Diffuse and Specular Interface Reflections by Color Image Segmentation,” Int'l J. Computer Vision, vol. 17, no. 3, pp. 249-272, 1996.
[2] P. Beckmann and A. Spizzochino, The Scattering of Electromagnetic Waves from Rough Surfaces. New York: Pergamon, 1963.
[3] M. Born and E. Wolf, Principles of Optics, seventh ed. Cambridge, 1999.
[4] A. Criminisi, S.B. Kang, R. Swaminathan, S. Szeliski, and P. Anandan, “Extracting Layers and Analyzing Their Specular Properties Using Epipolar Plane Image Analysis,” Technical Report MSR-TR-2002-19, Microsoft Research, 2002.
[5] M. D'Zmura and P. Lennie, “Mechanism of Color Constancy,” J. Optics Soc. Am. A, vol. 3, no. 10, pp. 1162-1672, 1986.
[6] B.V. Funt, M. Drew, and M. Brockington, “Recovering Shading from Color Images,” Proc. European Conf. Computer Vision (ECCV '92), pp. 124-132, 1992.
[7] R. Gershon, A.D. Jepson, and J.K. Tsotsos, “Ambient Illumination and the Determination of Material Changes,” J. Optics Soc. Am. A, vol. 3, no. 10, pp. 1700-1707, 1986.
[8] R.C. Gonzales and R.E. Woods, Digital Image Processing. Addison-Wesley, 1993.
[9] G. Healey and R. Kondepudy, “Radiometric CCD Camera Calibration and Noise Estimation,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 16, no. 3, pp. 267-276, Mar. 1994.
[10] J.M. Rubin and W.A. Richard, “Color Vision: Representing Material Categories,” AI Memo 764, MIT Artificial Intelligence Lab., 1984.
[11] G.J. Klinker, S.A. Shafer, and T. Kanade, “The Measurement of Highlights in Color Images,” Int'l J. Computer Vision, vol. 2, pp. 7-32, 1990.
[12] J.H. Lambert, Photometria Sive de Mensura de Gratibus Luminis, Colorum et Umbrae. Augsberg, Germany: Eberhard Klett, 1760.
[13] H.C. Lee, E.J. Breneman, and C.P. Schulte, “Modeling Light Reflection for Computer Color Vision,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 12, no. 4, pp. 402-409, Apr. 1990.
[14] S.W. Lee, “Understanding of Surface Reflections in Computer Vision by Color and Multiple Views,” PhD thesis, Univ. of Pennsylvania, 1991.
[15] S.W. Lee and R. Bajcsy, “Detection of Specularity Using Color and Multiple Views,” Image and Vision Computing, vol. 10, pp. 643-653, 1992.
[16] T.M. Lehmann and C. Palm, “Color Line Search for Illuminant Estimation in Real-World Scene,” J. Optics Soc. Am. A, vol. 18, no. 11, pp. 2679-2691, 2001.
[17] S. Lin, Y. Li, S.B. Kang, X. Tong, and H.Y. Shum, “Diffuse-Specular Separation and Depth Recovery from Image Sequences,” Proc. European Conf. Computer Vision (ECCV '02), pp. 210-224, 2002.
[18] S. Lin and H.Y. Shum, “Separation of Diffuse and Specular Reflection in Color Images,” Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR '01), 2001.
[19] D. Miyazaki, R.T. Tan, K. Hara, and K. Ikeuchi, “Polarization-Based Inverse Rendering from a Single View,” Proc. IEEE Int'l Conf. Computer Vision (ICCV '03), 2003.
[20] S.K. Nayar, X.S. Fang, and T. Boult, “Separation of Reflection Components Using Color and Polarization,” Int'l J. Computer Vision, vol. 21, no. 3, 1996.
[21] S.K. Nayar, K. Ikeuchi, and T. Kanade, “Surface Reflection: Physical and Geometrical Perspectives,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 13, no. 7, pp. 611-634, July 1991.
[22] M. Oren and S.K. Nayar, “Generalization of the Lambertian Model and Implications for Machine Vision,” Int'l J. Computer Vision, vol. 14, no. 3, pp. 227-251, 1995.
[23] J.P.S. Parkkinen, J. Hallikainen, and T. Jasskelainen, “Characteristic Spectra of Munsell Colors,” J. Optics Soc. Am. A, vol. 6, 1989.
[24] Y. Sato and K. Ikeuchi, “Temporal-Color Space Analysis of Reflection,” J. Optics Soc. Am. A, vol. 11, 1994.
[25] S. Shafer, “Using Color to Separate Reflection Components,” Color Research and Applications, vol. 10, pp. 210-218, 1985.
[26] R.T. Tan, K. Nishino, and K. Ikeuchi, “Color Constancy through Inverse Intensity Chromaticity Space,” J. Optics Soc. Am. A, vol. 21, no. 3, pp. 321-334, 2004.
[27] R.T. Tan, K. Nishino, and K. Ikeuchi, “Separating Reflection Components Based on Chromaticity and Noise Analysis,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 26, no. 10, Oct. 2004.
[28] K.E. Torrance and E.M. Sparrow, “Theory for Off-Specular Reflection from Roughened Surfaces,” J. Optics Soc. Am., vol. 57, pp. 1105-1114, 1966.
[29] L. Wolff, S.K. Nayar, and M. Oren, “Improved Diffuse Reflection Models for Computer Vision,” Int'l J. Computer Vision, vol. 30, no. 1, pp. 55-71, 1998.
[30] L.B. Wolff, “Polarization-Based Material Classification from Specular Reflection,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 12, no. 11, pp. 1059-1071, Nov. 1990.
[31] L.B. Wolff, “A Diffuse Reflectance Model for Smooth Dielectrics,” J. Optics Soc. Am. A, vol. 11, no. 11, pp. 2956-2968, 1994.
[32] L.B. Wolff and T. Boult, “Constraining Object Features Using Polarization Reflectance Model,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 13, no. 7, pp. 635-657, July 1991.

Index Terms:
Reflection components separation, specular reflection, diffuse reflection, dichromatic reflection model, chromaticity, specular-to-diffuse mechanism, specular-free image.
Citation:
Robby T. Tan, Katsushi Ikeuchi, "Separating Reflection Components of Textured Surfaces Using a Single Image," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 2, pp. 178-193, Feb. 2005, doi:10.1109/TPAMI.2005.36
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