Abstract
This paper presents a novel prior, radial bright channel (RBC) prior, for single image vignetting correction. The RBC prior is derived from a statistical property of vignetting-free images: for the pixels sharing the same radius in polar coordinates of an image, at least one pixel has a high intensity value at some color channel. Exploiting the prior, we can effectively estimate and correct the vignetting effect of a given image. We represent the vignetting effect as an 1D function of the distance from the optical center, and estimate the function using the RBC prior. As it works completely in 1D, our method provides high efficiency in terms of computation and storage costs. Experimental results demonstrate that our method runs an order of magnitude faster than previous work, while producing higher quality results of vignetting correction.
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Asada, N., Amano, A., Baba, M.: Photometric calibration of zoom lens systems. In: Proc. International Conference on Pattern Recognition, vol. 1, pp. 186–190 (1996)
Coleman, T., Li, Y.: An interior trust region approach for nonlinear minimization subject to bounds. SIAM Journal on Optimization 6(2), 418–445 (1996)
Goldman, D.B.: Vignette and exposure calibration and compensation. IEEE Trans. Pattern Analysis and Machine Intelligence 32(12), 2276–2288 (2010)
He, K., Sun, J., Tang, X.: Single image haze removal using dark channel prior. IEEE Trans. Pattern Analysis and Machine Intelligence 33(12), 2341–2353 (2011)
Juang, R., Majumder, A.: Photometric self-calibration of a projector-camera system. In: Proc. CVPR, pp. 1–8 (2007)
Kang, S.B., Weiss, R.: Can we calibrate a camera using an image of a flat, textureless Lambertian surface? In: Vernon, D. (ed.) ECCV 2000. LNCS, vol. 1843, pp. 640–653. Springer, Heidelberg (2000)
Kim, S.J., Pollefeys, M.: Robust radiometric calibration and vignetting correction. IEEE Trans. Pattern Analysis and Machine Intelligence 30(4), 562–576 (2008)
Kǒsecká, J., Zhang, W.: Video compass. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002, Part IV. LNCS, vol. 2353, pp. 476–490. Springer, Heidelberg (2002)
Kuthirummal, S., Agarwala, A., Goldman, D.B., Nayar, S.K.: Priors for large photo collections and what they reveal about cameras. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part IV. LNCS, vol. 5305, pp. 74–87. Springer, Heidelberg (2008)
Litvinov, A., Schechner, Y.: Addressing radiometric nonidealities: A unified framework. In: Proc. CVPR, pp. 52–59 (2005)
Lyu, S.: Single image vignetting correction with natural image statistics in derivative domains. In: Proc. ICIP (2010)
Sawchuk, A.: Real-time correction of intensity nonlinearities in imaging systems. IEEE Trans. on Computers C-26(1), 34–39 (1977)
Yu, W.: Practical anti-vignetting methods for digital cameras. IEEE Trans. on Consumer Electronics 50(4), 975–983 (2004)
Zheng, Y., Kambhamettu, C., Lin, S.: Single-image optical center estimation from vignetting and tangential gradient symmetry. In: Proc. CVPR, pp. 2058–2065 (2009)
Zheng, Y., Lin, S., Kambhamettu, C., Yu, J., Kang, S.B.: Single-image vignetting correction. IEEE Trans. Pattern Analysis and Machine Intelligence 31(12), 2243–2256 (2009)
Zheng, Y., Lin, S., Kang, S.B.: Single-image vignetting correction. In: Proc. CVPR, pp. 461–468 (2006)
Zheng, Y., Lin, S., Kang, S.B., Xiao, R., Gee, J.C., Kambhamettu, C.: Single-image vignetting correction from gradient distribution symmetries. IEEE Trans. Pattern Analysis and Machine Intelligence 35(6), 1480–1494 (2013)
Zheng, Y., Yu, J., Kang, S.B., Lin, S., Kambhamettu, C.: Single-image vignetting correction using radial gradient symmetry. In: Proc. CVPR, pp. 1–8 (2008)
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Cho, H., Lee, H., Lee, S. (2014). Radial Bright Channel Prior for Single Image Vignetting Correction. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds) Computer Vision – ECCV 2014. ECCV 2014. Lecture Notes in Computer Science, vol 8690. Springer, Cham. https://doi.org/10.1007/978-3-319-10605-2_13
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DOI: https://doi.org/10.1007/978-3-319-10605-2_13
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