Yönlü Toplam Deǧişinti Enküçültme Yöntemi ile Seyrek Örneklerden Imge Geriçatimi

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

doi:10.1109/SIU.2016.7495957

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

Department of Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 contribution	Image reconstruction from sparse samples using directional total variation minimization
Original language	Turkish
Title of host publication	2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1185-1188
Number of pages	4
ISBN (Electronic)	9781509016792
DOIs	https://doi.org/10.1109/SIU.2016.7495957
Publication status	Published - 20 Jun 2016
Event	24th Signal Processing and Communication Application Conference, SIU 2016 - Zonguldak, Turkey Duration: 16 May 2016 → 19 May 2016

Publication series

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

Conference

Conference	24th Signal Processing and Communication Application Conference, SIU 2016
Country/Territory	Turkey
City	Zonguldak
Period	16/05/16 → 19/05/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Access to Document

10.1109/SIU.2016.7495957

Cite this

Demircan-Türeyen, E., Kamaşak, M. E., & Bayram, I. (2016). Yönlü Toplam Deǧişinti Enküçültme Yöntemi ile Seyrek Örneklerden Imge Geriçatimi. In 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings (pp. 1185-1188). Article 7495957 (2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU.2016.7495957

Demircan-Türeyen, Ezgi ; Kamaşak, Mustafa E. ; Bayram, Ilker. / Yönlü Toplam Deǧişinti Enküçültme Yöntemi ile Seyrek Örneklerden Imge Geriçatimi. 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 1185-1188 (2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings).

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title = "Y{\"o}nl{\"u} Toplam Deǧi{\c s}inti Enk{\"u}{\c c}{\"u}ltme Y{\"o}ntemi ile Seyrek {\"O}rneklerden Imge Geri{\c c}atimi",

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.",

keywords = "convex optimization, directional total variation, image reconstruction, proximal splitting methods",

author = "Ezgi Demircan-T{\"u}reyen and Kama{\c s}ak, \{Mustafa E.\} and Ilker Bayram",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 24th Signal Processing and Communication Application Conference, SIU 2016 ; Conference date: 16-05-2016 Through 19-05-2016",

year = "2016",

month = jun,

day = "20",

doi = "10.1109/SIU.2016.7495957",

language = "T{\"u}rk{\c c}e",

series = "2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1185--1188",

booktitle = "2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings",

address = "United States",

}

Demircan-Türeyen, E, Kamaşak, ME & Bayram, I 2016, Yönlü Toplam Deǧişinti Enküçültme Yöntemi ile Seyrek Örneklerden Imge Geriçatimi. in 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings., 7495957, 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 1185-1188, 24th Signal Processing and Communication Application Conference, SIU 2016, Zonguldak, Turkey, 16/05/16. https://doi.org/10.1109/SIU.2016.7495957

Yönlü Toplam Deǧişinti Enküçültme Yöntemi ile Seyrek Örneklerden Imge Geriçatimi. / Demircan-Türeyen, Ezgi; Kamaşak, Mustafa E.; Bayram, Ilker.
2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. p. 1185-1188 7495957 (2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Yönlü Toplam Deǧişinti Enküçültme Yöntemi ile Seyrek Örneklerden Imge Geriçatimi

AU - Demircan-Türeyen, Ezgi

AU - Kamaşak, Mustafa E.

AU - Bayram, Ilker

PY - 2016/6/20

Y1 - 2016/6/20

N2 - 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.

AB - 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.

KW - convex optimization

KW - directional total variation

KW - image reconstruction

KW - proximal splitting methods

UR - https://www.scopus.com/pages/publications/84982797727

U2 - 10.1109/SIU.2016.7495957

DO - 10.1109/SIU.2016.7495957

M3 - Konferans katkısı

AN - SCOPUS:84982797727

T3 - 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings

SP - 1185

EP - 1188

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

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 24th Signal Processing and Communication Application Conference, SIU 2016

Y2 - 16 May 2016 through 19 May 2016

ER -

Demircan-Türeyen E, Kamaşak ME, Bayram I. Yönlü Toplam Deǧişinti Enküçültme Yöntemi ile Seyrek Örneklerden Imge Geriçatimi. In 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2016. p. 1185-1188. 7495957. (2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings). doi: 10.1109/SIU.2016.7495957

Yönlü Toplam Deǧişinti Enküçültme Yöntemi ile Seyrek Örneklerden Imge Geriçatimi

Abstract

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Bibliographical note

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