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Istituto di Scienza e Tecnologie dell'Informazione     
Yan Q., Kuruoglu E. E., Yang X., Xu Y., Kayabol K. Separating reflections from a single image using spatial smoothness and structure information. In: LVA/ICA 2010 - Latent Variable Analysis and Signal Separation. 9th International Conference (St. Malo, France, 27-30 September 2010). Proceedings, pp. 637 - 644. Vincent Vigneron, Vicente Zarzoso, Eric Moreau, Rémi Gribonval, Emmanuel Vincent (eds.). (Lecture Notes in Computer Science, vol. 6365). Springer, 2010.
 
 
Abstract
(English)
We adopt two priors to realize reflection separation from a single image, namely spatial smoothness, which is based on pixels' color dependency, and structure difference, which is got from different source images (transmitted image and reflected image) and different color channels of the same image. By analysing the optical model of reflection, we simplify the mixing matrix further and realize the method for getting spatially varying mixing coefficients. Based on the priors and using Gibbs sampling and appropriate probability density with Bayesian framework, our approach can achieve impressive results for many real world images that corrupted with reflections.
URL: http://www.springerlink.com/content/t297381505430v07/
DOI: 10.1007/978-3-642-15995-4_79
Subject Reflection cancellation
Bayesian estimation
Optical model
I.4.4 Restoration
I.4.9 Image Processing and Computer Vision. Applications
62M40 Random fields; image analysis
68U10 Image processing
62F15 Bayesian inference


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