Parameter estimation for LP regularized image deconvolution
Xu Zhou, Fugen Zhou, Xiangzhi Bai · 2015
Parameter estimation in Total Variation (TV) deblurring has been extensively studied in the literature during the last decade. However, few works have been done for parameter estimation in ℓp(0poutperforms TV and ℓ1in natural image deblurring. In this paper, by utilizing the Bayesian framework, we propose an adaptive fast iteratively reweighted least squares algorithm for ℓpregularized image deconvolution, which automatically estimates the unknown image and regularization parameter. Experiments show that the proposed method yields nearly optimal results and outperforms the state-of-the-art methods.