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

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

Bilgisayar Mühendisliği Bölümü

Istanbul Kultur University
Istanbul Technical University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

3 Atıf (Scopus)

Özet

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.

Tercüme edilen katkı başlığı	Image reconstruction from sparse samples using directional total variation minimization
Orijinal dil	Türkçe
Ana bilgisayar yayını başlığı	2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
Sayfalar	1185-1188
Sayfa sayısı	4
ISBN (Elektronik)	9781509016792
DOI'lar	https://doi.org/10.1109/SIU.2016.7495957
Yayın durumu	Yayınlandı - 20 Haz 2016
Etkinlik	24th Signal Processing and Communication Application Conference, SIU 2016 - Zonguldak, Türkiye Süre: 16 May 2016 → 19 May 2016

Yayın serisi

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

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	24th Signal Processing and Communication Application Conference, SIU 2016
Ülke/Bölge	Türkiye
Şehir	Zonguldak
Periyot	16/05/16 → 19/05/16

Bibliyografik not

Publisher Copyright:
© 2016 IEEE.

Keywords

convex optimization
directional total variation
image reconstruction
proximal splitting methods

Belgeye Erişim

10.1109/SIU.2016.7495957

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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). Makale 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",

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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, Türkiye, 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).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

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

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Keywords

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap