Title :
De-noising and enhancement for SAR oil slick based on SRAD
Author :
Suo, Van ; Guo, Hao
Author_Institution :
Sch. of Inf. Sci. & Technol., Dalian Maritime Univ., Dalian, China
Abstract :
Synthetic Aperture Radar (SAR) images are extensively used for the determination of oil spill accidents in the marine environment, and oil slick area in SAR image has uneven grayscale, block-shaped dim shadow and the ubiquity of speckle noise, which adversely affect target detection, classification and identification[1]. In order to research on SAR image enhancement, this paper respectively compare Lee filter, Kuan filter, Frost filter and other spatial filtering methods with Speckle Reducing Anisotropic Diffusion (SRAD) algorithm, experimental results show that spatial filtering methods make the edge of the target area blurred which adversely affect the target detection classification and identification, while SRAD algorithm works well de-noising the block-shaped area and has better effect on image enhancement.
Keywords :
diffusion; geophysical image processing; image classification; image denoising; marine accidents; marine pollution; object detection; oceanographic techniques; remote sensing by radar; synthetic aperture radar; Frost filter; Kuan filter; Lee filter; SAR image enhancement; SAR oil slick denoising; SAR oil slick enhancement; SRAD; block-shaped area; block-shaped dim shadow; image classification; marine environment; oil slick area; oil spill accidents; spatial filtering methods; speckle noise; speckle reducing anisotropic diffusion algorithm; synthetic aperture radar images; target detection; Image resolution; Lubricating oils; PSNR; Speckle Reducing Anisotropic Diffusion (SRAD); Synthetic Aperture Radar (SAR); image enhancement; oil slick image;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2011 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4577-1586-0
DOI :
10.1109/ICCSNT.2011.6182161