SAR Image Despeckling with Adaptive Multiscale Products Based on Directionlet Transform

Synthetic aperture radar (SAR) images are inherently affected by multiplicative speckle noise generated by radar coherent wave. In this paper, a new despeckling algorithm based on directionlets using multiscale products is proposed. We first take an anisotropic directionlet transform on the logarith...

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Main Authors: Yixiang Lu, Qingwei Gao, Dong Sun, Dexiang Zhang
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2013/197159
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spelling doaj-1977185ce49048d0afd96e4d29e4acaa2020-11-25T00:24:57ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472013-01-01201310.1155/2013/197159197159SAR Image Despeckling with Adaptive Multiscale Products Based on Directionlet TransformYixiang Lu0Qingwei Gao1Dong Sun2Dexiang Zhang3School of Electrical Engineering and Automation, Anhui University, Hefei 230601, ChinaSchool of Electrical Engineering and Automation, Anhui University, Hefei 230601, ChinaSchool of Electrical Engineering and Automation, Anhui University, Hefei 230601, ChinaSchool of Electrical Engineering and Automation, Anhui University, Hefei 230601, ChinaSynthetic aperture radar (SAR) images are inherently affected by multiplicative speckle noise generated by radar coherent wave. In this paper, a new despeckling algorithm based on directionlets using multiscale products is proposed. We first take an anisotropic directionlet transform on the logarithmically transformed SAR images and multiply the coefficients at adjacent scales to enhance the details of image under consideration. Then, different from traditional thresholding methods, a threshold is applied to the multiscale products of the directionlet coefficients to suppress noise. Since the multiplication amplifies the significant features of signal and dilute noise, the proposed method reduces noise effectively while preserving edge structures. Finally, we compare the performance of the proposed algorithm with other despeckling methods applied to synthetic image and real SAR images. Experimental results demonstrate the effectiveness of the proposed method in SAR images despeckling.http://dx.doi.org/10.1155/2013/197159
collection DOAJ
language English
format Article
sources DOAJ
author Yixiang Lu
Qingwei Gao
Dong Sun
Dexiang Zhang
spellingShingle Yixiang Lu
Qingwei Gao
Dong Sun
Dexiang Zhang
SAR Image Despeckling with Adaptive Multiscale Products Based on Directionlet Transform
Mathematical Problems in Engineering
author_facet Yixiang Lu
Qingwei Gao
Dong Sun
Dexiang Zhang
author_sort Yixiang Lu
title SAR Image Despeckling with Adaptive Multiscale Products Based on Directionlet Transform
title_short SAR Image Despeckling with Adaptive Multiscale Products Based on Directionlet Transform
title_full SAR Image Despeckling with Adaptive Multiscale Products Based on Directionlet Transform
title_fullStr SAR Image Despeckling with Adaptive Multiscale Products Based on Directionlet Transform
title_full_unstemmed SAR Image Despeckling with Adaptive Multiscale Products Based on Directionlet Transform
title_sort sar image despeckling with adaptive multiscale products based on directionlet transform
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2013-01-01
description Synthetic aperture radar (SAR) images are inherently affected by multiplicative speckle noise generated by radar coherent wave. In this paper, a new despeckling algorithm based on directionlets using multiscale products is proposed. We first take an anisotropic directionlet transform on the logarithmically transformed SAR images and multiply the coefficients at adjacent scales to enhance the details of image under consideration. Then, different from traditional thresholding methods, a threshold is applied to the multiscale products of the directionlet coefficients to suppress noise. Since the multiplication amplifies the significant features of signal and dilute noise, the proposed method reduces noise effectively while preserving edge structures. Finally, we compare the performance of the proposed algorithm with other despeckling methods applied to synthetic image and real SAR images. Experimental results demonstrate the effectiveness of the proposed method in SAR images despeckling.
url http://dx.doi.org/10.1155/2013/197159
work_keys_str_mv AT yixianglu sarimagedespecklingwithadaptivemultiscaleproductsbasedondirectionlettransform
AT qingweigao sarimagedespecklingwithadaptivemultiscaleproductsbasedondirectionlettransform
AT dongsun sarimagedespecklingwithadaptivemultiscaleproductsbasedondirectionlettransform
AT dexiangzhang sarimagedespecklingwithadaptivemultiscaleproductsbasedondirectionlettransform
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