PARAMETER ESTIMATION IN TOTAL VARIATION BLIND DECONVOLUTION

In this paper we present a methodology for parameter estimation in total variation (TV) blind deconvolution. By formulating the prob- lem in a Bayesian framework, the unknown image, blur and the model parameters are simultaneously estimated. The resulting al- gorithms provide approximations to the posterior distributions of the unknowns by utilizing variational distribution approximations. We show that some of the current approaches towards TV-based blind deconvolution are special cases of our formulation. Experi- mental results are provided to demonstrate the performance of the algorithms.