Title :
SAR image despeckling using undecimated directional filter banks and mean shift
Author :
Zhang, Gong ; Shi, Wenhua ; Xu, Jing ; Li, Ning ; Smith, Mark J T
Author_Institution :
Coll. of Inf. Sci. & Technol., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
Abstract :
The granular appearance of speckle noise in synthetic aperture radar (SAR) imagery can make it difficult to visually and automatically interpret SAR data. Speckle reduction is a prerequisite for many SAR image processing tasks. In this paper, a novel method of SAR image despeckling is presented that uses undecimated directional filter banks (UDFB) and mean shift clustering. The UDFB is obtained by manipulating the resampling matrices in the Bamberger directional filter banks (DFB), such that low computational complexity is preserved, while achieving shift invariance that could be useful in pattern recognition and image denoising applications. A nonparametric estimator of the density gradient is employed in the joint spatial-range domain of the directional bands obtained by the UDFB. Examples included at the end of the paper illustrate typical performance results obtained using this method.
Keywords :
filtering theory; image denoising; pattern recognition; radar imaging; synthetic aperture radar; SAR image despeckling; image denoising; image processing; pattern recognition; speckle noise; synthetic aperture radar imagery; undecimated directional filter banks; Channel bank filters; Discrete wavelet transforms; Educational institutions; Filter bank; Filtering; Image analysis; Information science; Signal analysis; Speckle; Synthetic aperture radar; Synthetic aperture radar; directional filter banks; mean shift; speckle;
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.2009.5414270