A Bayesian Markov chain Monte Carlo solution of the bilinear problem

Many problems in imaging reduce to a desire to identify physically significant components within a set of images gathered during the variation of a parameter. We present a new method to identify physically meaningful regions in a series of images through the application of Bayesian statistics within a Markov chain Monte Carlo sampler. The method finds the physically meaningful bilinear solution appropriate to the problem.