Sparsity-driven despeckling method with low memory usage Düsük Hafiza Kullanimli Seyreklik-Güdümlü Benek Gürültü Azaltma Yöntemi

Özcan C., Şen B. , Nar F.

24th Signal Processing and Communication Application Conference, SIU 2016, Zonguldak, Turkey, 16 - 19 May 2016, pp.1329-1332 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2016.7495993
  • City: Zonguldak
  • Country: Turkey
  • Page Numbers: pp.1329-1332


Speckle noise which is inherent to Synthetic Aperture Radar (SAR) imaging makes it difficult to detect targets and recognize spatial patterns on earth. Thus, despeckling is critical and used as a preprocessing step for smoothing homogeneous regions while preserving features such as edges and point scatterers. In this study, a low-memory version of the previously proposed sparsity-driven despeckling (SDD) method is proposed. All steps of the method are parallelized using OpenMP on CPU and CUDA on GPU. Execution time and despeckling performance are shown using real-world SAR images.