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Publication details

Blind deconvolution of images with model discrepancies using maximum a posteriori estimation with heavy-tailed priors

Conference Paper (international conference)

Kotera Jan, Šroubek Filip


serial: Digital Photography XI

action: Digital Photography and Mobile Imaging XI, (San Francisco, US, 09.02.2015-10.02.2015)

project(s): 938213/2013, GA UK, M100751201, GA AV ČR

keywords: image blind deconvolution, image deblurring, blur estimation, pixel saturation, boundary artifacts

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abstract (eng):

Single image blind deconvolution aims to estimate the unknown blur from a single observed blurred image and recover the original sharp image. Such task is severely ill-posed and typical approaches involve some heuristic or other steps without clear mathematical explanation to arrive at an acceptable solution. We show that a straight- forward maximum a posteriori estimation incorporating sparse priors and mechanism to deal with boundary artifacts, combined with an efficient numerical method can produce results which compete with or outperform much more complicated state-of-the-art methods. Our method is naturally extended to deal with overexposure in low-light photography, where linear blurring model is violated.

RIV: JD

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Last modification: 21.12.2012
Institute of Information Theory and Automation