Complexity-Regularized Denoising of Poisson-Corrupted Data

In this paper, we apply the complexity–regularization principle to Poisson imaging. We formulate a natural distortion measure in 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.