The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.01 - Jan. (2013 vol.35)
pp: 144-156
Joon-Young Lee , Dept. of Electr. Eng., KAIST, Daejeon, South Korea
Y. Matsushita , Microsoft Res. Asia, Beijing, China
Boxin Shi , Ikeuchi Lab., Univ. of Tokyo, Tokyo, Japan
In So Kweon , Dept. of Electr. Eng., KAIST, Daejeon, South Korea
K. Ikeuchi , Ikeuchi Lab., Univ. of Tokyo, Tokyo, Japan
ABSTRACT
We present a robust radiometric calibration framework that capitalizes on the transform invariant low-rank structure in the various types of observations, such as sensor irradiances recorded from a static scene with different exposure times, or linear structure of irradiance color mixtures around edges. We show that various radiometric calibration problems can be treated in a principled framework that uses a rank minimization approach. This framework provides a principled way of solving radiometric calibration problems in various settings. The proposed approach is evaluated using both simulation and real-world datasets and shows superior performance to previous approaches.
INDEX TERMS
Image color analysis, Radiometry, Calibration, Noise, Vectors, Cameras, Minimization,low-rank structure, Radiometric calibration, camera response function, rank minimization
CITATION
Joon-Young Lee, Y. Matsushita, Boxin Shi, In So Kweon, K. Ikeuchi, "Radiometric Calibration by Rank Minimization", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.35, no. 1, pp. 144-156, Jan. 2013, doi:10.1109/TPAMI.2012.66
REFERENCES
[1] P. Debevec and J. Malik, "Recovering High Dynamic Range Radiance Maps from Photographs," Proc. ACM Siggraph, pp. 369-378, 1997.
[2] T. Mitsunaga and S.K. Nayar, "Radiometric Self Calibration," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 374-380, 1999.
[3] S. Lin, J. Gu, S. Yamazaki, and H.-Y. Shum, "Radiometric Calibration from a Single Image," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 938-945, 2004.
[4] B. Shi, Y. Matsushita, Y. Wei, C. Xu, and P. Tan, "Self-Calibrating Photometric Stereo," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1118-1125, 2010.
[5] S.J. Kim and M. Pollefeys, "Robust Radiometric Calibration and Vignetting Correction," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 30, no. 4, pp. 562-576, Apr. 2008.
[6] S. Mann and R. Picard, "On Being 'Undigital' with Digital Cameras: Extending Dynamic Range by Combining Differently Exposed Pictures," Proc. 48th Ann. Conf. Information Systems and Technology, pp. 422-428, 1995.
[7] M. Grossberg and S.K. Nayar, "Modeling the Space of Camera Response Functions," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 26, no. 10, pp. 1272-1282, Oct. 2004.
[8] S.K. Nayar and T. Mitsunaga, "High Dynamic Range Imaging: Spatially Varying Pixel Exposures," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 472-479, 2000.
[9] S. Mann and R. Mann, "Quantigraphic Imaging: Estimating the Camera Response and Exposures from Differently Exposed Images," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 842-849, 2001.
[10] M. Grossberg and S.K. Nayar, "Determining the Camera Response from Images: What Is Knowable?" IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 11, pp. 1455-1467, Nov. 2003.
[11] A. Litvinov and Y.Y. Schechner, "Addressing Radiometric Nonidealities: A Unified Framework," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 52-59, 2005.
[12] H. Farid, "Blind Inverse Gamma Correction," IEEE Trans. Image Processing, vol. 10, no. 10, pp. 1428-1433, Oct. 2001.
[13] Y. Tsin, V. Ramesh, and T. Kanade, "Statistical Calibration of CCD Imaging Process," Proc. IEEE Int'l Conf. Computer Vision, pp. 480-487, 2001.
[14] C. Pal, R. Szeliski, M. Uyttendale, and N. Jojic, "Probability Models for High Dynamic Range Imaging," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 173-180, 2004.
[15] T.-T. Ng, S.-F. Chang, and M.-P. Tsui, "Using Geometry Invariants for Camera Response Function Estimation," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1-8, 2007.
[16] Y. Matsushita and S. Lin, "Radiometric Calibration from Noise Distributions," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1-8, 2007.
[17] J. Takamatsu, Y. Matsushita, and K. Ikeuchi, "Estimating Camera Response Functions Using Probabilistic Intensity Similarity," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1-8, 2008.
[18] J. Takamatsu, Y. Matsushita, and K. Ikeuchi, "Estimating Radiometric Response Functions from Image Noise Variance," Proc. European Conf. Computer Vision, pp. 623-637, 2008.
[19] S. Lin and L. Zhang, "Determining the Radiometric Response Function from a Single Grayscale Image," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 66-73, 2005.
[20] B. Wilburn, H. Xu, and Y. Matsushita, "Radiometric Calibration Using Temporal Irradiance Mixtures," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1-7, 2008.
[21] C. Manders, C. Aimone, and S. Mann, "Camera Response Function Recovery from Different Illuminations of Identical Subject Matter," Proc. Int'l Conf. Image Processing, pp. 2965-2968, 2004.
[22] K. Shafique and M. Shah, "Estimation of the Radiometric Response Functions of a Color Camera from Differently Illuminated Images," Proc. Int'l Conf. Image Processing, pp. 2339-2342, 2004.
[23] S.J. Kim, J.-M. Frahm, and M. Pollefeys, "Radiometric Calibration with Illumination Change for Outdoor Scene Analysis," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1-8, 2008.
[24] M. Turk and A. Pentland, "Eigenfaces for Recognition," J. Cognitive Neuroscience, vol. 3, no. 1, pp. 71-86, 1991.
[25] C. Tomasi and T. Kanade, "Shape and Motion from Image Streams under Orthography: A Factorization Method," Int'l J. Computer Vision, vol. 9, no. 2, pp. 137-154, 1992.
[26] H. Hayakawa, "Photometric Stereo under a Light Source with Arbitrary Motion," J. Optical Soc. Am., vol. 11, no. 11, pp. 3079-3089, 1994.
[27] Y. Peng, A. Ganesh, J. Wright, W. Xu, and Y. Ma, "RASL: Robust Alignment by Sparse and Low-Rank Decomposition for Linearly Correlated Images," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 763-770, 2010.
[28] M. Paladini, A. Bartoli, and L. Agapito, "Sequential Non-Rigid Structure-from-Motion with the 3D-Implicit Low-Rank Shape Model," Proc. European Conf. Computer Vision, pp. 15-28, 2010.
[29] Z. Zhang, A. Ganesh, X. Liang, and Y. Ma, "Tilt: Transform Invariant Low-Rank Textures," Proc. Asian Conf. Computer Vision, pp. 314-328, 2010.
[30] L. Wu, A. Ganesh, B. Shi, Y. Matsushita, Y. Wang, and Y. Ma, "Robust Photometric Stereo via Low-Rank Matrix Completion and Recovery," Proc. Asian Conf. Computer Vision, pp. 703-717, 2010.
[31] Z. Zhang, Y. Matsushita, and Y. Ma, "Camera Calibration with Lens Distortion from Low-Rank Textures," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 2321-2328, 2011.
[32] J.-Y. Lee, B. Shi, Y. Matsushita, I.-S. Kweon, and K. Ikeuchi, "Radiometric Calibration by Transform Invariant Low-Rank Structure," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 2337-2344, 2011.
[33] J. Wright, A. Ganesh, S. Rao, Y. Peng, and Y. Ma, "Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices by Convex Optimization," Proc. Neural Information Processing Systems, 2009.
[34] Y. Hwang, J.-S. Kim, and I.S. Kweon, "Difference-Based Image Noise Modeling Using Skellam Distribution," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 34, no. 7, pp. 1329-1341, July 2012.
[35] A. Chakrabarti, D. Scharstein, and T. Zickler, "An Empirical Camera Model for Internet Color Vision," Proc. British Machine Vision Conf., 2009.
[36] M. Grossberg and S.K. Nayar, "What Is the Space of Camera Response Functions?" Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 602-609, 2003.
[37] H.T. Lin, S.J. Kim, S. Susstrunk, and M.S. Brown, "Revisiting Radiometric Calibration for Color Computer Vision," Proc. IEEE Int'l Conf. Computer Vision, 2011.
[38] J. Nelder and R. Mead, "A Simplex Method for Function Minimization," Computer J., vol. 7, pp. 308-313, 1965.
72 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool