Separation of Weak Reflection from a Single Superimposed Image

It is an inherently ill-posed problem to separate a single superimposed image into a reflection image and a transmission image. In this letter, a novel algorithm is proposed based on the prior knowledge that edges of weak reflection are always smoother than most edges of observed objects. To filter out the edges of weak reflection, an MRF-EM (Markov Random Field and Expectation Maximization) framework is proposed. In the MRF model, a data energy function is established based on the edge smoothness metric GPS (Gradient Profile Sharpness), and a spatial smoothness energy function is formulated using a weighted Potts model. Moreover, the parameters in the data energy function are updated using the EM algorithm. Experimental results demonstrate that the proposed algorithm can produce superior separation results with less residuals and color distortions compared to state-of-the-art methods.

[1]  Anat Levin,et al.  User Assisted Separation of Reflections from a Single Image Using a Sparsity Prior , 2004, ECCV.

[2]  Rama Chellappa,et al.  Direct Analytical Methods for Solving Poisson Equations in Computer Vision Problems , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

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

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

[5]  Rabab Kreidieh Ward,et al.  A New Scheme for Robust Gradient Vector Estimation in Color Images , 2011, IEEE Transactions on Image Processing.

[6]  Changshui Zhang,et al.  Blind Separation of Superimposed Moving Images Using Image Statistics. , 2012, IEEE transactions on pattern analysis and machine intelligence.

[7]  Sei-Wang Chen,et al.  Interference reflection separation from a single image , 2009, 2009 Workshop on Applications of Computer Vision (WACV).

[8]  Kai Chen,et al.  Image super-resolution based on a novel edge sharpness prior , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

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

[10]  Richard Szeliski,et al.  Layer extraction from multiple images containing reflections and transparency , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[11]  Richard Szeliski,et al.  Stereo matching with linear superposition of layers , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Adrian N. Evans,et al.  A morphological gradient approach to color edge detection , 2006, IEEE Transactions on Image Processing.

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

[14]  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).