Fast quadratic-linear approximated L1-norm for SAR image despeckling
Yazarlar (2)
Doç. Dr. Fatih Nar Ankara Yıldırım Beyazıt Üniversitesi, Türkiye
Doç. Dr. Ferhat ATASOY Karabük Üniversitesi, Türkiye
| Bildiri Türü | Tebliğ/Bildiri | Bildiri Dili | Türkçe |
| Bildiri Alt Türü | Tam Metin Olarak Yayınlanan Tebliğ (Ulusal Kongre/Sempozyum) | ||
| Bildiri Niteliği | Alanında Hakemli Ulusal Kongre/Sempozyum | ||
| Kongre Adı | International Conference on Advanced Technologies, Computer Engineering and Science (ICATCES 2018) | ||
| Kongre Tarihi | 11-05-2018 / | ||
| Basıldığı Ülke | Türkiye | Basıldığı Şehir | Karabük |
| UAK Araştırma Alanları |
Bilgisayar Yazılımı
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| Özet |
| Speckle noise, inherent in synthetic aperture radar (SAR) images, degrades the performance of the various SAR image analysis tasks. Thus, speckle noise reduction is a critical preprocessing step for smoothing homogeneous regions while preserving details. Therefore, recently, SDD-QL method was proposed which is a variational approach where i1-norm total variation regularization term is approximated in a quadratic-linear manner to increase despeckling accuracy with decreased computation time. In this study, we propose a simple and efficient mechanism to increase the speed of SDD-QL method up to order of magnitude while obtaining the same despeckling result. Computational efficiency and despeckling performance of the proposed method are compared to the SDD-QL method on real-world SAR images. |
| Anahtar Kelimeler |