Graph-cut-based compression algorithm for compressed-sensed image acquisition

Julide Gulen Alaydin; Seden Hazal Gulen; Maria Trocan; Behcet Ugur Toreyin

doi:10.1109/SIU.2014.6830726

Graph-cut-based compression algorithm for compressed-sensed image acquisition

Julide Gulen Alaydin, Seden Hazal Gulen, Maria Trocan, Behcet Ugur Toreyin

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

1 Atıf (Scopus)

Özet

The purpose of the paper is to find the best quantizer allocation for compressed-sensed acquired images, by using a graph-cut quantizer allocation method. The compressed sensed acquisition is realized in a block-based manner, using a random projection matrix, and on the obtained block measurements a graph-cut-based quantizer allocation method is applied, in order to further reduce the bitrate associated to the measurements. Finally, the quantized measurements are reconstructed using a Smooth Projected Landweber recovery method. The proposed compression method for compressed sensed acquisition shows better results when compared to JPEG2000.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings
Yayınlayan	IEEE Computer Society
Sayfalar	2310-2313
Sayfa sayısı	4
ISBN (Basılı)	9781479948741
DOI'lar	https://doi.org/10.1109/SIU.2014.6830726
Yayın durumu	Yayınlandı - 2014
Harici olarak yayınlandı	Evet
Etkinlik	2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Trabzon, Turkey Süre: 23 Nis 2014 → 25 Nis 2014

Yayın serisi

Adı	2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings

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???event.eventtypes.event.conference???	2014 22nd Signal Processing and Communications Applications Conference, SIU 2014
Ülke/Bölge	Turkey
Şehir	Trabzon
Periyot	23/04/14 → 25/04/14

Belgeye Erişim

10.1109/SIU.2014.6830726

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Alaydin, J. G., Gulen, S. H., Trocan, M., & Toreyin, B. U. (2014). Graph-cut-based compression algorithm for compressed-sensed image acquisition. In 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings (pp. 2310-2313). Makale 6830726 (2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings). IEEE Computer Society. https://doi.org/10.1109/SIU.2014.6830726

Alaydin, Julide Gulen ; Gulen, Seden Hazal ; Trocan, Maria et al. / Graph-cut-based compression algorithm for compressed-sensed image acquisition. 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings. IEEE Computer Society, 2014. pp. 2310-2313 (2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings).

@inproceedings{9901447a8da04ca88fab910ce2c350bf,

title = "Graph-cut-based compression algorithm for compressed-sensed image acquisition",

abstract = "The purpose of the paper is to find the best quantizer allocation for compressed-sensed acquired images, by using a graph-cut quantizer allocation method. The compressed sensed acquisition is realized in a block-based manner, using a random projection matrix, and on the obtained block measurements a graph-cut-based quantizer allocation method is applied, in order to further reduce the bitrate associated to the measurements. Finally, the quantized measurements are reconstructed using a Smooth Projected Landweber recovery method. The proposed compression method for compressed sensed acquisition shows better results when compared to JPEG2000.",

author = "Alaydin, \{Julide Gulen\} and Gulen, \{Seden Hazal\} and Maria Trocan and Toreyin, \{Behcet Ugur\}",

year = "2014",

doi = "10.1109/SIU.2014.6830726",

language = "English",

isbn = "9781479948741",

series = "2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings",

publisher = "IEEE Computer Society",

pages = "2310--2313",

booktitle = "2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings",

address = "United States",

note = "2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 ; Conference date: 23-04-2014 Through 25-04-2014",

}

Alaydin, JG, Gulen, SH, Trocan, M & Toreyin, BU 2014, Graph-cut-based compression algorithm for compressed-sensed image acquisition. in 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings., 6830726, 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings, IEEE Computer Society, pp. 2310-2313, 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014, Trabzon, Turkey, 23/04/14. https://doi.org/10.1109/SIU.2014.6830726

Graph-cut-based compression algorithm for compressed-sensed image acquisition. / Alaydin, Julide Gulen; Gulen, Seden Hazal; Trocan, Maria et al.
2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings. IEEE Computer Society, 2014. p. 2310-2313 6830726 (2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings).

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

TY - GEN

T1 - Graph-cut-based compression algorithm for compressed-sensed image acquisition

AU - Alaydin, Julide Gulen

AU - Gulen, Seden Hazal

AU - Trocan, Maria

AU - Toreyin, Behcet Ugur

PY - 2014

Y1 - 2014

N2 - The purpose of the paper is to find the best quantizer allocation for compressed-sensed acquired images, by using a graph-cut quantizer allocation method. The compressed sensed acquisition is realized in a block-based manner, using a random projection matrix, and on the obtained block measurements a graph-cut-based quantizer allocation method is applied, in order to further reduce the bitrate associated to the measurements. Finally, the quantized measurements are reconstructed using a Smooth Projected Landweber recovery method. The proposed compression method for compressed sensed acquisition shows better results when compared to JPEG2000.

AB - The purpose of the paper is to find the best quantizer allocation for compressed-sensed acquired images, by using a graph-cut quantizer allocation method. The compressed sensed acquisition is realized in a block-based manner, using a random projection matrix, and on the obtained block measurements a graph-cut-based quantizer allocation method is applied, in order to further reduce the bitrate associated to the measurements. Finally, the quantized measurements are reconstructed using a Smooth Projected Landweber recovery method. The proposed compression method for compressed sensed acquisition shows better results when compared to JPEG2000.

UR - https://www.scopus.com/pages/publications/84903788902

U2 - 10.1109/SIU.2014.6830726

DO - 10.1109/SIU.2014.6830726

M3 - Conference contribution

AN - SCOPUS:84903788902

SN - 9781479948741

T3 - 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings

SP - 2310

EP - 2313

BT - 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings

PB - IEEE Computer Society

T2 - 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014

Y2 - 23 April 2014 through 25 April 2014

ER -

Alaydin JG, Gulen SH, Trocan M, Toreyin BU. Graph-cut-based compression algorithm for compressed-sensed image acquisition. In 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings. IEEE Computer Society. 2014. p. 2310-2313. 6830726. (2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings). doi: 10.1109/SIU.2014.6830726

Graph-cut-based compression algorithm for compressed-sensed image acquisition

Özet

Yayın serisi

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

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

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