SAR Image Enhancement using Particle Filters
Shared by Deniz Gencaga, updated on Sep 22, 2010
Summary
- Author(s) :
- Deniz Gencaga, E.E. Kuruoglu, A. Ertuzun
- Abstract
In this paper, we propose a novel approach to reduce the noise in Synthetic Aperture Radar (SAR) images using particle filters. Interpretation of SAR images is a difficult problem, since they are contaminated with a multiplicative noise, which is known as the “Speckle Noise”. In literature, the general approach for removing
the speckle is to use the local statistics, which are computed in a square window. Here, we propose to use particle filters, which is a sequential Bayesian technique. The proposed method also uses the local statistics to denoise the images. Since this is a Bayesian
approach, the computed statistics of the window can be exploited as a priori information. Moreover, particle filters are sequential methods, which are more appropriate to handle the heterogeneous structure of the image. Computer simulations show that the proposed method provides better edge-preserving results with
satisfactory speckle removal, when compared to the results obtained by Gamma Maximum a posteriori (MAP) filter.
- Publication Name
- Proceedings of the ESA-EUSC 2005: Image Information Mining – Theory and Application to Earth Observation
- Publication Location
- Frascati, Italy
- Year Published
- 2005
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