Blind Image Deblurring using the l0 Gradient Prior

Jérémy Anger, Gabriele Facciolo, Mauricio Delbracio

Abstract: Many blind image deblurring methods rely on unnatural image priors that are explicitly designed to restore salient image structures, necessary to estimate the blur kernel. In this article, we analyze the blur kernel estimation method introduced by Pan and Su in 2013 that uses an l0 prior on the gradient image. We present deconvolution results using the estimated blur kernels. Our experiments show the effectiveness of the method as well as some of its shortcomings.