Iterative Self-Dual Reconstruction on Radar Image Recovery [electronic resource].
- Berkeley, Calif. : Lawrence Berkeley National Laboratory, 2010.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
- Physical Description:
- 6 : digital, PDF file
- Additional Creators:
- Lawrence Berkeley National Laboratory and United States. Department of Energy. Office of Scientific and Technical Information
- Restrictions on Access:
- Free-to-read Unrestricted online access
- Imaging systems as ultrasound, sonar, laser and synthetic aperture radar (SAR) are subjected to speckle noise during image acquisition. Before analyzing these images, it is often necessary to remove the speckle noise using filters. We combine properties of two mathematical morphology filters with speckle statistics to propose a signal-dependent noise filter to multiplicative noise. We describe a multiscale scheme that preserves sharp edges while it smooths homogeneous areas, by combining local statistics with two mathematical morphology filters: the alternating sequential and the self-dual reconstruction algorithms. The experimental results show that the proposed approach is less sensitive to varying window sizes when applied to simulated and real SAR images in comparison with standard filters.
- Report Numbers:
- E 1.99:lbnl-3846e
- Other Subject(s):
- Published through SciTech Connect.
IEEE 2009 Workshop on Applications of Computer Vision (WACV).
Martins, Charles; Medeiros, Fatima; Ushizima, Daniela; Bezerra, Francisco; Marques, Regis; Mascarenhas, Nelson.
Computational Research Division
- Funding Information:
View MARC record | catkey: 14653930