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Proceedings Paper

Wavelet-based multiscale anisotropic diffusion for speckle reduction and edge enhancement
Author(s): Yi Wang; Ruiqing Niu; Ke Wu
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Paper Abstract

In order to improve signal-to-noise ratio (SNR) and image quality, this paper introduces a wavelet-based multiscale anisotropic diffusion algorithm to remove speckle noise and enhance edges. In our algorithm, we use the tool of wavelet to construct a linear scale-space for the speckle image. Due to the smoothing functionality of the scaling function, the wavelet-based multiscale representation of the speckle image is much more stationary than the raw speckle image. Noise is mostly located in the finest scale and tends to decrease as the scale increases. Furthermore, a robust speckle reduction anisotropic diffusion (SRAD) is to be proposed and we perform the improved SRAD on the stationary scale-space rather than on the rough speckle image domain. Qualitative experiments based on a speckle Synthetic aperture radar (SAR) image show the elegant characteristics of edge-preserving filtering versus the traditional adaptive filters. Quantitative analyses, based on the first order statistics and Equivalent Number of Looks, confirm the validity and effectiveness of the proposed algorithm.

Paper Details

Date Published: 30 October 2009
PDF: 9 pages
Proc. SPIE 7494, MIPPR 2009: Multispectral Image Acquisition and Processing, 74940I (30 October 2009); doi: 10.1117/12.832844
Show Author Affiliations
Yi Wang, China Univ. of Geosciences (China)
Ruiqing Niu, China Univ. of Geosciences (China)
Ke Wu, China Univ. of Geosciences (China)


Published in SPIE Proceedings Vol. 7494:
MIPPR 2009: Multispectral Image Acquisition and Processing
Faxiong Zhang; Faxiong Zhang, Editor(s)

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