Defocus inpainting

Paolo Favaro, Enrico Grisan

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

5 Citations (Scopus)

Abstract

In this paper, we propose a method to restore a single image affected by space-varying blur. The main novelty of our method is the use of recurring patterns as regularization during the restoration process. We postulate that restored patterns in the deblurred image should resemble other sharp details in the input image. To this purpose, we establish the correspondence of regions that are similar up to Gaussian blur. When two regions are in correspondence, one can perform deblurring by using the sharpest of the two as a proposal. Our solution consists of two steps: First, estimate correspondence of similar patches and their relative amount of blurring; second, restore the input image by imposing the similarity of such recurring patterns as a prior. Our approach has been successfully tested on both real and synthetic data.

Original languageEnglish
Title of host publicationComputer Vision - ECCV 2006, 9th European Conference on Computer Vision, Proceedings
PublisherSpringer Nature
Pages349-359
Number of pages11
ISBN (Print)3540338349, 9783540338345
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event9th European Conference on Computer Vision, ECCV 2006 - Graz, Austria
Duration: 7 May 200613 May 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3952 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th European Conference on Computer Vision, ECCV 2006
Country/TerritoryAustria
CityGraz
Period7/05/0613/05/06

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