Motion Estimation and Deblurring of Fast Moving Objects

0494139 - ÚTIA 2019 RIV US eng C - Conference Paper (international conference)
Kotera, Jan - Šroubek, Filip
Motion Estimation and Deblurring of Fast Moving Objects.
Proceedings of the 25th IEEE International Conference on Image Processing 2018. Piscataway: IEEE, 2018, s. 2860-2864. ISBN 978-1-4799-7062-9.
[IEEE International Conference on Image Processing 2018 (ICIP 2018) /25./. Atény (GR), 07.10.2018-10.10.2018]
R&D Projects: GA ČR GA18-05360S
Grant - others:GA UK(CZ) SVV2017260452
Institutional support: RVO:67985556
Keywords : blind deblurring * object deblurring * motion estimation * alternating minimization
OECD category: Computer hardware and architecture
http://library.utia.cas.cz/separaty/2018/ZOI/sroubek-0494139.pdf

Image deblurring is one of the standard problems in image processing. Recently, this area of research is dominated by blind deblurring, where neither the sharp image nor the blur are known. The majority of works, however, target scenarios where the captured scene is static and the blur is caused by camera motion, i.e. the whole image is blurred. In this work we address a similar yet different scenario: an object moves in front of a static background. Such object is blurred due to motion while the background is sharp and partially occluded by the object. The problem of blind deblurring in such setting has not been properly addressed in literature. We formally define the problem, discuss its solvability, and explain why it cannot be viewed as a special case of classical blind de-blurring. We propose a solution to the presented problem for a particular class of motions and demonstrate results on real data.
Permanent Link: http://hdl.handle.net/11104/0289350