Blind Image Deblurring using the l0 Gradient Prior
Jérémy Anger, Gabriele Facciolo, Mauricio Delbracio
→ BibTeX
@article{ipol.2019.243,
    title   = {{Blind Image Deblurring using the l0 Gradient Prior}},
    author  = {Anger, Jérémy and Facciolo, Gabriele and Delbracio, Mauricio},
    journal = {{Image Processing On Line}},
    volume  = {9},
    pages   = {124--142},
    year    = {2019},
    doi     = {10.5201/ipol.2019.243},
}
% if your bibliography style doesn't support doi fields:
    note    = {\url{https://doi.org/10.5201/ipol.2019.243}}
published
2019-03-12
reference
Jérémy Anger, Gabriele Facciolo, and Mauricio Delbracio, Blind Image Deblurring using the l0 Gradient Prior, Image Processing On Line, 9 (2019), pp. 124–142. https://doi.org/10.5201/ipol.2019.243

Communicated by Jean-Michel Morel and Miguel Colom
Demo edited by Jérémy Anger

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.

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