Separation of layers from images containing multiple reflections and transparency using cyclic permutation

In the paper, we propose a new method for blind separation of an arbitrary number of images from a set of their linear mixtures with unknown coefficients. This approach is as follows. We first introduce a novel multiple correlation between one image and a set of multiple images. Then this multiple correlation leads us to provide a set of simultaneous linear equations for updating each mixture of images. Finally, source images are recovered by iterating between solving the sets of equations and cyclically permuting the mixtures of images. The technique can be applied for extracting multiple layers from images containing multiple reflections and transparency.