Synthetic aperture radar image processing using cellular neural networks

Sedef Kent; Osman Nuri Ucan; Tolga Ensar

doi:10.1109/RAST.2003.1303925

Synthetic aperture radar image processing using cellular neural networks

Sedef Kent
, Osman Nuri Ucan
, Tolga Ensar

Elektronik ve Hab.Müh.Bölümü

Istanbul University

Araştırma çıktısı: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › Hakemli

Özet

In this paper, Cellular Neural Networks (CNNs) have been applied to noisy Synthetic Aperture Radar (SAR) image to improve its performance and appearance. The image has been obtained from Erzurum, Turkey. Because of the importance of imaging quality and appearance for remote sensing applications, CNN has been applied to data for image processing applications that for noise filtering and edge detection. In training, Recurrent Perceptron Learning Algorithm (RPLA) is used as a learning algorithm. According to templates SAR- image has been tested and obtained satisfactory results.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	RAST 2003 - Proceedings of International Conference on Recent Advances in Space Technologies
Editörler	S. Kurnaz, Fuat Ince, S. Onbasioglu
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
Sayfalar	308-310
Sayfa sayısı	3
ISBN (Elektronik)	0780381424, 9780780381421
DOI'lar	https://doi.org/10.1109/RAST.2003.1303925
Yayın durumu	Yayınlandı - 2003
Etkinlik	International Conference on Recent Advances in Space Technologies, RAST 2003 - Istanbul, Türkiye Süre: 20 Kas 2003 → 22 Kas 2003

Yayın serisi

Adı	RAST 2003 - Proceedings of International Conference on Recent Advances in Space Technologies

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

???event.eventtypes.event.conference???	International Conference on Recent Advances in Space Technologies, RAST 2003
Ülke/Bölge	Türkiye
Şehir	Istanbul
Periyot	20/11/03 → 22/11/03

Bibliyografik not

Publisher Copyright:
© 2003 IEEE.

Belgeye Erişim

10.1109/RAST.2003.1303925

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Kent, S., Ucan, O. N., & Ensar, T. (2003). Synthetic aperture radar image processing using cellular neural networks. In S. Kurnaz, F. Ince, & S. Onbasioglu (Eds.), RAST 2003 - Proceedings of International Conference on Recent Advances in Space Technologies (pp. 308-310). Makale 1303925 (RAST 2003 - Proceedings of International Conference on Recent Advances in Space Technologies). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RAST.2003.1303925

Kent, Sedef ; Ucan, Osman Nuri ; Ensar, Tolga. / Synthetic aperture radar image processing using cellular neural networks. RAST 2003 - Proceedings of International Conference on Recent Advances in Space Technologies. editör / S. Kurnaz ; Fuat Ince ; S. Onbasioglu. Institute of Electrical and Electronics Engineers Inc., 2003. pp. 308-310 (RAST 2003 - Proceedings of International Conference on Recent Advances in Space Technologies).

@inproceedings{d7937a3e77e64fec99c0c011b1e33515,

title = "Synthetic aperture radar image processing using cellular neural networks",

abstract = "In this paper, Cellular Neural Networks (CNNs) have been applied to noisy Synthetic Aperture Radar (SAR) image to improve its performance and appearance. The image has been obtained from Erzurum, Turkey. Because of the importance of imaging quality and appearance for remote sensing applications, CNN has been applied to data for image processing applications that for noise filtering and edge detection. In training, Recurrent Perceptron Learning Algorithm (RPLA) is used as a learning algorithm. According to templates SAR- image has been tested and obtained satisfactory results.",

author = "Sedef Kent and Ucan, \{Osman Nuri\} and Tolga Ensar",

note = "Publisher Copyright: {\textcopyright} 2003 IEEE.; International Conference on Recent Advances in Space Technologies, RAST 2003 ; Conference date: 20-11-2003 Through 22-11-2003",

year = "2003",

doi = "10.1109/RAST.2003.1303925",

language = "English",

series = "RAST 2003 - Proceedings of International Conference on Recent Advances in Space Technologies",

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

pages = "308--310",

editor = "S. Kurnaz and Fuat Ince and S. Onbasioglu",

booktitle = "RAST 2003 - Proceedings of International Conference on Recent Advances in Space Technologies",

address = "United States",

}

Kent, S, Ucan, ON & Ensar, T 2003, Synthetic aperture radar image processing using cellular neural networks. in S Kurnaz, F Ince & S Onbasioglu (eds), RAST 2003 - Proceedings of International Conference on Recent Advances in Space Technologies., 1303925, RAST 2003 - Proceedings of International Conference on Recent Advances in Space Technologies, Institute of Electrical and Electronics Engineers Inc., pp. 308-310, International Conference on Recent Advances in Space Technologies, RAST 2003, Istanbul, Türkiye, 20/11/03. https://doi.org/10.1109/RAST.2003.1303925

Synthetic aperture radar image processing using cellular neural networks. / Kent, Sedef; Ucan, Osman Nuri; Ensar, Tolga.
RAST 2003 - Proceedings of International Conference on Recent Advances in Space Technologies. ed. / S. Kurnaz; Fuat Ince; S. Onbasioglu. Institute of Electrical and Electronics Engineers Inc., 2003. p. 308-310 1303925 (RAST 2003 - Proceedings of International Conference on Recent Advances in Space Technologies).

Araştırma çıktısı: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › Hakemli

TY - GEN

T1 - Synthetic aperture radar image processing using cellular neural networks

AU - Kent, Sedef

AU - Ucan, Osman Nuri

AU - Ensar, Tolga

PY - 2003

Y1 - 2003

N2 - In this paper, Cellular Neural Networks (CNNs) have been applied to noisy Synthetic Aperture Radar (SAR) image to improve its performance and appearance. The image has been obtained from Erzurum, Turkey. Because of the importance of imaging quality and appearance for remote sensing applications, CNN has been applied to data for image processing applications that for noise filtering and edge detection. In training, Recurrent Perceptron Learning Algorithm (RPLA) is used as a learning algorithm. According to templates SAR- image has been tested and obtained satisfactory results.

AB - In this paper, Cellular Neural Networks (CNNs) have been applied to noisy Synthetic Aperture Radar (SAR) image to improve its performance and appearance. The image has been obtained from Erzurum, Turkey. Because of the importance of imaging quality and appearance for remote sensing applications, CNN has been applied to data for image processing applications that for noise filtering and edge detection. In training, Recurrent Perceptron Learning Algorithm (RPLA) is used as a learning algorithm. According to templates SAR- image has been tested and obtained satisfactory results.

UR - https://www.scopus.com/pages/publications/84945395388

U2 - 10.1109/RAST.2003.1303925

DO - 10.1109/RAST.2003.1303925

M3 - Conference contribution

AN - SCOPUS:84945395388

T3 - RAST 2003 - Proceedings of International Conference on Recent Advances in Space Technologies

SP - 308

EP - 310

BT - RAST 2003 - Proceedings of International Conference on Recent Advances in Space Technologies

A2 - Kurnaz, S.

A2 - Ince, Fuat

A2 - Onbasioglu, S.

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - International Conference on Recent Advances in Space Technologies, RAST 2003

Y2 - 20 November 2003 through 22 November 2003

ER -

Kent S, Ucan ON, Ensar T. Synthetic aperture radar image processing using cellular neural networks. In Kurnaz S, Ince F, Onbasioglu S, editörler, RAST 2003 - Proceedings of International Conference on Recent Advances in Space Technologies. Institute of Electrical and Electronics Engineers Inc. 2003. p. 308-310. 1303925. (RAST 2003 - Proceedings of International Conference on Recent Advances in Space Technologies). doi: 10.1109/RAST.2003.1303925

Synthetic aperture radar image processing using cellular neural networks

Özet

Yayın serisi

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

Bibliyografik not

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap