Separating Reflections from a Single Image Using Spatial Smoothness and Structure Information

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.

[1]  Michal Irani,et al.  Separating Transparent Layers through Layer Information Exchange , 2004, ECCV.

[2]  Anat Levin,et al.  User Assisted Separation of Reflections from a Single Image Using a Sparsity Prior , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Bülent Sankur,et al.  Bayesian Separation of Images Modeled With MRFs Using MCMC , 2009, IEEE Transactions on Image Processing.

[4]  Edward H. Adelson,et al.  Separating reflections and lighting using independent components analysis , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[5]  Arie Yeredor,et al.  Blind Separation of Reflections With Relative Spatial Shifts , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[6]  Bülent Sankur,et al.  Image Source Separation Using Color Channel Dependencies , 2009, ICA.

[7]  Changshui Zhang,et al.  Blindly separating mixtures of multiple layers with spatial shifts , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[8]  Emil Wolf,et al.  Principles of Optics: Contents , 1999 .

[9]  Yehoshua Y. Zeevi,et al.  Sparse ICA for blind separation of transmitted and reflected images , 2005, Int. J. Imaging Syst. Technol..

[10]  Y. Weiss,et al.  Separating reflections from a single image using local features , 2004, CVPR 2004.

[11]  Changshui Zhang,et al.  Blind separation of superimposed images with unknown motions , 2009, CVPR.