SAR image despeckling: based on non-local means with non-subsample Shearlet and directional windows
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Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University ,Shaanxi,Xi’an,Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University ,Shaanxi,Xi’an,Department of Applied Mathematics, Xidian University, Shaanxi, Xi’an, 710071, China,Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University ,Shaanxi,Xi’an,Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University ,Shaanxi,Xi’an

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    Abstract:

    Good performance has been obtained by extending traditional image denoising algorithm from local computation model to non-local one with non-local means algorithm. For synthesis aperture radar (SAR) image, however, the similarity measured by observations and isotropic window is not robust and without direction, which is bad for capturing the structure of image. In this paper, Non-subsample Shearlet feature and directional neighborhood based non-local means algorithm are proposed. Experimental results demonstrated that the improved non-local means algorithm can not only remove the speckle, but also preserve the geometrical structure information which is essential for understanding and interpretation of SAR image.

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ZHANG Xiao-Hua, CHEN Jia-Wei, MENG Hong-Yun, JIAO Li-Cheng, SUN Xiang. SAR image despeckling: based on non-local means with non-subsample Shearlet and directional windows[J]. Journal of Infrared and Millimeter Waves,2012,31(2):159~165

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History
  • Received:March 06,2011
  • Revised:June 24,2011
  • Adopted:April 25,2011
  • Online: April 23,2012
  • Published: