Speckle Noise Removal for Synthetic Aperture Radar Imagery Based on Statistics Filters and Nonlinearing Function

Synthetic Aperture Radar (SAR) images are contaminated by multiplicative noise, due to the coherence of the radar wavelength, labeled as speckle noise which results in an important reduction in the efficiency of target detection and classification algorithms . In this paper the corrupted pixels are...

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Main Author: E kbal H. Ali
Format: Article
Language:English
Published: Unviversity of Technology- Iraq 2012-07-01
Series:Engineering and Technology Journal
Subjects:
Online Access:https://etj.uotechnology.edu.iq/article_60861_57d48143dd4e62765ae87b9cc3e0d1fa.pdf
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author E kbal H. Ali
author_facet E kbal H. Ali
author_sort E kbal H. Ali
collection DOAJ
description Synthetic Aperture Radar (SAR) images are contaminated by multiplicative noise, due to the coherence of the radar wavelength, labeled as speckle noise which results in an important reduction in the efficiency of target detection and classification algorithms . In this paper the corrupted pixels are replaced by an estimated value using the simple filter based statistics filters with nonlinear function which are worked at the same time to reduce the speckle noise without blurring edges or other features in SAR imagery. Quantitative and qualitative comparisons of the results obtained by the proposed method with the results achieved from the other speckle noise reduction filters demonstrate its higher performance for speckle reduction with preserving high frequency features (edges) in SAR images.
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spelling doaj.art-afb0c17cbd334360aa58f96920201aad2024-02-04T17:39:46ZengUnviversity of Technology- IraqEngineering and Technology Journal1681-69002412-07582012-07-0130132252226410.30684/etj.30.13.760861Speckle Noise Removal for Synthetic Aperture Radar Imagery Based on Statistics Filters and Nonlinearing FunctionE kbal H. AliSynthetic Aperture Radar (SAR) images are contaminated by multiplicative noise, due to the coherence of the radar wavelength, labeled as speckle noise which results in an important reduction in the efficiency of target detection and classification algorithms . In this paper the corrupted pixels are replaced by an estimated value using the simple filter based statistics filters with nonlinear function which are worked at the same time to reduce the speckle noise without blurring edges or other features in SAR imagery. Quantitative and qualitative comparisons of the results obtained by the proposed method with the results achieved from the other speckle noise reduction filters demonstrate its higher performance for speckle reduction with preserving high frequency features (edges) in SAR images.https://etj.uotechnology.edu.iq/article_60861_57d48143dd4e62765ae87b9cc3e0d1fa.pdfsar imagesnoisespeckle filteringadaptive filteredge measure
spellingShingle E kbal H. Ali
Speckle Noise Removal for Synthetic Aperture Radar Imagery Based on Statistics Filters and Nonlinearing Function
Engineering and Technology Journal
sar images
noise
speckle filtering
adaptive filter
edge measure
title Speckle Noise Removal for Synthetic Aperture Radar Imagery Based on Statistics Filters and Nonlinearing Function
title_full Speckle Noise Removal for Synthetic Aperture Radar Imagery Based on Statistics Filters and Nonlinearing Function
title_fullStr Speckle Noise Removal for Synthetic Aperture Radar Imagery Based on Statistics Filters and Nonlinearing Function
title_full_unstemmed Speckle Noise Removal for Synthetic Aperture Radar Imagery Based on Statistics Filters and Nonlinearing Function
title_short Speckle Noise Removal for Synthetic Aperture Radar Imagery Based on Statistics Filters and Nonlinearing Function
title_sort speckle noise removal for synthetic aperture radar imagery based on statistics filters and nonlinearing function
topic sar images
noise
speckle filtering
adaptive filter
edge measure
url https://etj.uotechnology.edu.iq/article_60861_57d48143dd4e62765ae87b9cc3e0d1fa.pdf
work_keys_str_mv AT ekbalhali specklenoiseremovalforsyntheticapertureradarimagerybasedonstatisticsfiltersandnonlinearingfunction