Yönlü Toplam Deǧişinti Enküçültme Yöntemi ile Seyrek Örneklerden Imge Geriçatimi

Translated title of the contribution: Image reconstruction from sparse samples using directional total variation minimization

Ezgi Demircan-Türeyen, Mustafa E. Kamaşak, Ilker Bayram

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

3 Citations (Scopus)

Abstract

This paper considers reconstruction of missing pixels and formulates the problem under directional total variation (DTV) regularization. In order to devise an algorithm, forward-backward splitting method is used as a convex optimization tool, in conjunction with a fast projected gradient-based algorithm. The results are compared with the results of TV-based setting, and the utility of using DTV is shown in terms of accuracy, when an image with a dominant direction is the case.

Translated title of the contributionImage reconstruction from sparse samples using directional total variation minimization
Original languageTurkish
Title of host publication2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1185-1188
Number of pages4
ISBN (Electronic)9781509016792
DOIs
Publication statusPublished - 20 Jun 2016
Event24th Signal Processing and Communication Application Conference, SIU 2016 - Zonguldak, Turkey
Duration: 16 May 201619 May 2016

Publication series

Name2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings

Conference

Conference24th Signal Processing and Communication Application Conference, SIU 2016
Country/TerritoryTurkey
CityZonguldak
Period16/05/1619/05/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

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