The problem of separating a non-rectangular foreground image from a background image is a classical problem in image processing and analysis, known as Matting or keying. A common example is a film frame where an actor is extracted from the background to later be placed on a different background. Compositing of these objects against a new background is one of the most common operations in the creation of visual effects. When the original background is of non-constant color the Matting becomes an under determined problem, for which a unique solution cannot be found. This thesis describes a framework for computing mattes from images with backgrounds of non-constant color, using Bayesian statistics.