SAR Image Despeckling Algorithm Using Non-Local Means with Adaptive Filtering Strength

Lei ZHU; Jingman LI; Yang PAN; Yuchun LIU; Xiao HU

doi:10.11999/JEIT200099

Volume 43 Issue 5

May 2021

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Lei ZHU, Jingman LI, Yang PAN, Yuchun LIU, Xiao HU. SAR Image Despeckling Algorithm Using Non-Local Means with Adaptive Filtering Strength[J]. Journal of Electronics & Information Technology, 2021, 43(5): 1258-1266. doi: 10.11999/JEIT200099

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Lei ZHU, Jingman LI, Yang PAN, Yuchun LIU, Xiao HU. SAR Image Despeckling Algorithm Using Non-Local Means with Adaptive Filtering Strength[J]. Journal of Electronics & Information Technology, 2021, 43(5): 1258-1266. doi: 10.11999/JEIT200099

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SAR Image Despeckling Algorithm Using Non-Local Means with Adaptive Filtering Strength

doi: 10.11999/JEIT200099

Lei ZHU^{1
,
,},
Jingman LI¹,
Yang PAN¹,
Yuchun LIU^{1, 2},
Xiao HU¹

1.
School of Electronics and Information, Xi’an Polytechnic University, Xi’an 710048, China
2.
School of Mechanical and Electrical Engineering, Zhoukou Normal University, Zhoukou 466001, China

Funds: The National Natural Science Foundation of China (61971339), The Shaanxi Provincial Key Research and Development Program (2019GY-113), The Xi’an Science and Technology Bureau Innovation and Guidance Program (201805030YD8CG14(6))

Received Date: 2020-02-11
Rev Recd Date: 2020-09-09

Available Online: 2020-09-15

Publish Date: 2021-05-18

Abstract

Abstract

A new Non-Local Means (NLM) despeckling algorithm (AFS-NLM) with Adaptive Filtering Strength (AFS) is proposed to improve the performance of reducing multiplicative speckle and preserving the edges in SAR images. A modified Kuan filtering coefficient which can better characterize the homogeneous and edge regions of SAR image is formed by using the local mean and variance calculated in the Frost filtered image to improve the estimation of SAR image scene parameters. An improved NLM which adapts to the multiplicative noise characteristics is constructed by the new similarity measurement parameter estimated by the local mean ratio and the new adaptive decay factor estimated by the improved Kuan filtering coefficient. A new weighted filtering model which can automatically adjust the filtering strength is formed. In the new model, the improved NLM filters controlled by the skew smoothing parameters and the skew edge protection parameters are used to replace the local average value of pixels and the gray value of pixels in the classic Kuan filter model as weighting items, and the adaptive adjustment factor constructed by the improved Kuan filter coefficient is used to weight the two items. Experimental results and comparisons with several advanced despeckling algorithms in recent years show that the proposed algorithm has better speckle suppression and edge preservation performance.
- SAR image,
- Speckle suppression,
- Adaptive Filtering Strength (AFS),
- Non-Local Means (NLM),
- Improved Kuan filtering

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References(23)

References

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