Institute of Information Theory and Automation

You are here

Bibliography

Conference Paper (international conference)

Motion Blur Prior

Šroubek Filip, Kotera Jan

: 2020 IEEE International Conference on Image Processing (ICIP), p. 928-932

: 2020 IEEE International Conference on Image Processing (ICIP), (Abu Dhabi, AE, 20201025)

: GA18-05360S, GA ČR

: deblurring, deconvolution, motion blur, atomic norm, convolutional sparse coding

: 10.1109/ICIP40778.2020.9191316

: http://library.utia.cas.cz/separaty/2020/ZOI/sroubek-0533761.pdf

(eng): We have proposed a novel methodology for generating priors that favor motion blur. 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.

: JD

: 20206

2019-01-07 08:39