Early-exit optimization using mixed norm despeckling for SAR images SAR Görüntülerde Karmaşik Norm Kullanarak Gürültü Azaltimi Için Erken Çikiş Eniyilemesi


Özcan C., Şen B. , Nar F.

2015 23rd Signal Processing and Communications Applications Conference, SIU 2015, Malatya, Turkey, 16 - 19 May 2015, pp.779-782 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2015.7129944
  • City: Malatya
  • Country: Turkey
  • Page Numbers: pp.779-782

Abstract

Speckle noise which is inherent to Synthetic Aperture Radar (SAR) imaging obstructs various image exploitation tasks such as edge detection, segmentation, change detection, and target recognition. Speckle reduction is generally used as a first step which has to smooth out homogeneous regions while preserving edges and point scatterers. In remote sensing applications, efficiency of computational load and memory consumption of despeckling must be improved for SAR images. In this paper, an early-exit total variation approach is proposed and this approach combines the l(1)-norm and the l(2)-norm in order to improve despeckling quality while keeping execution times of algorithm reasonably short. Speckle reduction performance, execution time and memory consumption are shown using spot mode SAR images.