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Motion Blur Prior

Citation Author(s):
F. Sroubek, J. Kotera
Submitted by:
Filip Sroubek
Last updated:
4 November 2020 - 9:07am
Document Type:
Presentation Slides
Document Year:
2020
Event:
Presenters:
Filip Sroubek

Abstract

Priors play an important role of regularizers in image deblurring algorithms. Image priors are frequently studied and many forms were proposed in the literature. Blur priors are considered less important and the most common forms are simple uniform distributions with domain constraints. We propose a more informative blur prior based on the notion of atomic norm which favors blurs composed of line segments and is suitable for motion blur. The prior is formulated as a linear program that can be inserted into any optimization task. Evaluation is conducted on blind deblurring of moving objects.

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