  Photographs taken through a glass surface often contain an approximately
linear superposition of reflected and transmitted layers. Decomposing an image
into these layers is generally an ill-posed task and the use of an additional
image prior and user provided cues is presently necessary in order to obtain
good results. Current annotation approaches rely on a strong sparsity
assumption. For images with significant texture this assumption does not
typically hold, thus rendering the annotation process unviable. In this paper
we show that using a Gaussian Mixture Model patch prior, the correct local
decomposition can almost always be found as one of 100 likely modes of the
posterior. Thus, the user need only choose one of these modes in a sparse set
of patches and the decomposition may then be completed automatically. We
demonstrate the performance of our method using synthesized and real reflection
images.
