Title :
Early-exit optimization using mixed norm despeckling for SAR images
Author :
Ozcan, Caner ; Sen, Baha ; Nar, Fatih
Author_Institution :
Bilgisayar Muhendisligi Bolumu, Karabuk Univ., Karabük, Turkey
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 l1-norm and the l2-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.
Keywords :
edge detection; electromagnetic wave scattering; image denoising; image segmentation; object recognition; optimisation; radar imaging; remote sensing by radar; speckle; synthetic aperture radar; SAR imaging; change detection; computational load; despeckling quality; early-exit optimization; edge detection; image exploitation tasks; memory consumption; mixed norm despeckling; point scatterers; remote sensing applications; speckle noise; speckle reduction; spot mode SAR images; synthetic aperture radar; target recognition; Graphics processing units; Noise; Radar imaging; Speckle; Synthetic aperture radar; Wiener filters; CUDA; GPU; Synthetic aperture radar; early-exit; optimization; speckle noise;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2015 23th
Conference_Location :
Malatya
DOI :
10.1109/SIU.2015.7129944