Title :
Structure-preserving speckle reduction of SAR images using nonlocal means filters
Author :
Yang, Xuezhi ; Clausi, David A.
Author_Institution :
Sch. of Comput. & Inf., Hefei Univ. of Technol., Hefei, China
Abstract :
This paper proposes a structure-preserving speckle reduction (SPSR) algorithm for synthetic aperture radar (SAR) images by exploiting self-similarity of structural patterns based on nonlocal means filter. The SPSR algorithm is featured by discerning pixels of similar structural patterns, which is crucial for a despeckling process to avoid blurring image structure. To alleviate the impact of speckle noise to similarity measure, a two-stage filtering scheme is introduced into the SPSR algorithm. Filtering at the first stage aims at an accurate approximation of true structural similarity, followed by the filtering at the second stage to group pixels with similar neighborhood in a large area. Compared to the traditional Lee filter, enhanced Lee filter and the speckle reducing anisotropic diffusion (SRAD), evaluation results have shown that the SPSR algorithm substantially improves the despeckling performance especially on structure preservation and speckle reduction in homogeneous regions.
Keywords :
filtering theory; radar imaging; synthetic aperture radar; SAR images; enhanced Lee filter; image denoising; nonlocal means filters; speckle reducing anisotropic diffusion; structure-preserving speckle reduction; synthetic aperture radar images; two-stage filtering scheme; Additive white noise; Anisotropic magnetoresistance; Gaussian noise; Image converters; Image restoration; Information filtering; Information filters; Noise reduction; Speckle; Synthetic aperture radar; Synthetic aperture radar (SAR); nonlocal means; speckle reduction;
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2009.5414502