SAR Image Enhancement using Particle Filters
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.
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Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| accrualPeriodicity | irregular |
| bureauCode |
[ "026:00" ] |
| contactPoint |
{ "fn": "Deniz Gencaga", "@type": "vcard:Contact", "hasEmail": "mailto:dgencaga@gmail.com" } |
| description | 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. |
| distribution |
[ { "@type": "dcat:Distribution", "title": "ESA_EUSC_conference_GENCAGA_etal.pdf", "format": "PDF", "mediaType": "application/pdf", "description": "SAR image enhancement using particle filtering", "downloadURL": "https://c3.nasa.gov/dashlink/static/media/publication/ESA_EUSC_conference_GENCAGA_etal.pdf" } ] |
| identifier | DASHLINK_212 |
| issued | 2010-09-22 |
| keyword |
[ "ames", "dashlink", "nasa" ] |
| landingPage | https://c3.nasa.gov/dashlink/resources/212/ |
| modified | 2025-03-31 |
| programCode |
[ "026:029" ] |
| publisher |
{ "name": "Dashlink", "@type": "org:Organization" } |
| title | SAR Image Enhancement using Particle Filters |
