Motion Blur Prior

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 proposed curve rior is formulated as a linear program that can be inserted into any optimization task.

A Matlab implementation of the curve prior and a demo script testing it on the problem of deblurring fast moving objects (deblatting) is provided here.

Duration: 2017-2020
Contact person: Filip Sroubek
Involved people: Jan Kotera


  • Šroubek Filip, Kotera Jan : Motion Blur Prior, Proceedings of the 27th IEEE International Conference on Image Processing 2020, ICIP 2020, [2020]
Sroubek_ICIP2020_supp.zip201.41 KB