Fast total variation deconvolution for blurred image contaminated by Poisson noise

• The algorithm focuses on restoring blurred image contaminated by Poisson image.
• The algorithm uses the variable splitting technique to simply the problem.
• The algorithm runs very fast and the restored image is of high quality.
• The algorithm is easy to be extended to solve other optimization problem.

In this paper, we present a fast non-blind deconvolution method for restoring blurred images contaminated by Poisson noise. The problem is formulated by finding the minimizer of the negative logarithmic Poisson log-likelihood combined with the total variation (TV). To attack the challenging task, we adopt the well-known variable splitting and penalty technique to convert the problem into two easier sub-problems: one is a modified TV regularized deconvolution and the other is a simple convex optimization problem. Experimental results show that the proposed method runs very fast and the quality of the restored image is comparable with that of some state of the art methods.