Complexity-regularized denoising of Poisson-corrupted data

Abstract

We apply the complexity-regularization principle to Poisson imaging. We formulate a natural distortion measure in the image space, and present a connection between complexity-regularized estimation and rate-distortion theory. For computational tractability, we apply constrained coders such as JPEG or SPIHT to solve the optimization problem approximately. Also, we design a simple predictive coder which lends itself well to our optimization problem.