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.