Restoration of images with piecewise space-variant blur

Leah Bar*, Nir Sochen, Nahum Kiryati

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We address the problem of space-variant image deblurring, where different parts of the image are blurred by different blur kernels. Assuming a region-wise space variant point spread function, we first solve the problem for the case of known blur kernels and known boundaries between the different blur regions in the image. We then generalize the method to the challenging case of unknown boundaries between the blur domains. Using variational and level set techniques, the image is processed globally. The space-variant deconvolution process is stabilized by a unified common regularizer, thus preserving discontinuities between the differently restored image regions. In the case where the blurred subregions are unknown, a segmentation procedure is performed using an evolving level set function, guided by edges and image derivatives.

Original languageEnglish
Title of host publicationScale Space and Variational Methods in Computer Vision, First International Conference, SSVM 2007, Proceedings
PublisherSpringer Verlag
Pages533-544
Number of pages12
ISBN (Print)9783540728221
DOIs
StatePublished - 2007
Event1st International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2007 - Ischia, Italy
Duration: 30 May 20072 Jun 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4485 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2007
Country/TerritoryItaly
CityIschia
Period30/05/072/06/07

Fingerprint

Dive into the research topics of 'Restoration of images with piecewise space-variant blur'. Together they form a unique fingerprint.

Cite this