EM-type algorithms for image reconstruction with background emission and poisson noise

Abstract

Obtaining high quality images is very important in many areas of applied sciences. In this paper, we proposed general robust expectation maximization (EM)-Type algorithms for image reconstruction when the measured data is corrupted by Poisson noise. This method is separated into two steps: EM and regularization. In order to overcome the contrast reduction introduced by some regularizations, we suggested EM-Type algorithms with Bregman iteration by applying a sequence of modified EM-Type algorithms. The numerical experiments show the effectiveness of these methods in different applications. © 2011 Springer-Verlag.