A wavelet-based quadratic extension method for image deconvolution in the presence of poisson noise

Iterative optimization algorithms such as the forward-backward and Douglas-Rachford algorithms have recently gained much popularity since they provide efficient solutions to a wide class of non-smooth convex minimization problems arising in signal/image recovery. However, when images are degraded by a convolution operator and a Poisson noise, a particular attention must be paid to the associated minimization problem. To solve it, we propose a new optimization method which consists of two nested iterative steps. The effectiveness of the proposed method is demonstrated via numerical comparisons.

• Type: Conference
• Year: 2009
• Where: ICASSP
• Authors: Nelly Pustelnik, Caroline Chaux, Jean-Christophe Pesquet
• Keywords: ICASSP 2009, Iterative Optimization Algorithms, Minimization Problem, Non-smooth Convex Minimization, Signal Processing