Iterative Filtering of SAR Image Based on Speckle Statistical Characteristic Preservation

LI Yu; WANG Shu-yun; ZHAO Quan-hua

doi:10.12263/DZXB.20201281

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Iterative Filtering of SAR Image Based on Speckle Statistical Characteristic Preservation

PAPERS | 更新时间：2025-12-08

- Iterative Filtering of SAR Image Based on Speckle Statistical Characteristic Preservation
- ACTA ELECTRONICA SINICA Vol. 49, Issue 9, Pages: 1809-1817(2021)
- 作者机构：
  
  辽宁工程技术大学测绘与地理科学学院遥感科学与应用研究所, 辽宁阜新 123000
- 作者简介：
- 基金信息：
- DOI：10.12263/DZXB.20201281
  CLC： TP751
- Received：16 November 2020，
  
  Revised：2021-04-07，
  
  Published：25 September 2021
- 稿件说明：
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李玉,王姝运,赵泉华.基于斑点统计特性保持的SAR影像迭代滤波[J].电子学报,2021,49(09):1809-1817.

LI Yu,WANG Shu-yun,ZHAO Quan-hua.Iterative Filtering of SAR Image Based on Speckle Statistical Characteristic Preservation[J].ACTA ELECTRONICA SINICA,2021,49(09):1809-1817.
李玉,王姝运,赵泉华.基于斑点统计特性保持的SAR影像迭代滤波[J].电子学报,2021,49(09):1809-1817. DOI： 10.12263/DZXB.20201281.

LI Yu,WANG Shu-yun,ZHAO Quan-hua.Iterative Filtering of SAR Image Based on Speckle Statistical Characteristic Preservation[J].ACTA ELECTRONICA SINICA,2021,49(09):1809-1817. DOI： 10.12263/DZXB.20201281.

摘要

合成孔径雷达（Synthetic Aperture Radar，SAR）影像中的斑点现象是地物后向散射信号相互干扰产生的，其虽然类似噪声却涉及地物目标的散射特征.同一地物目标的散射特征可通过斑点统计分布模型来刻画，因此降噪过程中可通过恢复影像斑点的统计分布特性来保留斑点包含的地物散射信息.基于该思想，提出一种基于斑点统计特性保持的SAR影像迭代滤波算法.该算法假设给定SAR影像的统计分布函数是先验已知的，即建模为混合Gamma分布，其分布参数可利用影像的像素值估计；接着基于构建的混合Gamma分布模型，运用EM（Expectation Maximization）算法分割影像中的同质区域；再针对不同同质区域，选取拟合误差较大的灰度级，根据分割结果计算像素值为该灰度级的像素的密度，判断其是否是异常像素，并对异常像素运用Frost滤波器进行降噪.重复上述步骤，直到滤波后的影像直方图较好地服从统计分布函数.GF‑3和Radarsat‑2 SAR影像数据实验结果表明，该算法在保证影像质量的前提下，不仅能获得较好的统计建模结果，而且较好地抑制了相干斑噪声，实现影像降噪.

Abstract

The speckle phenomenon in synthetic aperture radar (SAR) images is caused by the mutual interference of backscattering signals of ground objects. Although it is similar to noise

it involves the scattering characteristics of ground objects. The scattering characteristics of the same ground object can be described by the speckle statistical distribution model. Therefore

in the process of noise reduction

the scattering information of the ground object contained in the speckle can be preserved by restoring the statistical distribution characteristics of speckle. Based on this idea

an iterative filtering method of SAR image based on speckle statistical characteristic preservation is proposed. The proposed method assumes that the statistical distribution function of a given SAR image is known a priori

namely the mixture Gamma distribution

and its distribution parameters can be estimated by the pixel values of the image. Then

the EM（Expectation Maximization） algorithm is used to segment the SAR image based on the mixture Gamma distribution

so as to obtain the homogeneous regions in the image. Subsequently

for different homogeneous regions

select the gray levels with larger fitting errors

calculate the densities of the pixels whose values are the gray levels according to the segmentation results

and judge whether they are abnormal pixels

and the abnormal pixels are filtered by Frost filter. Repeat above procedure until the histogram of filtered image fits the statistical distribution function well. Experimental results of GF-3 and Radarsat-2 SAR image show that

on the premise of maintaining image quality

the proposed method can not only obtain better statistical modeling results

but also suppress speckle well and achieve image denoising.

关键词

Keywords

references

蒋李兵 , 王壮 , 雷琳 , 等 . 基于模型迭代匹配的单幅高分辨SAR图像遮挡建筑物高度估计方法 [J]. 通信学报 , 2013 , 34 ( 3 ): 68 - 75 .

JIANG Li-bin , WANG Zhuang , LEI Lin , et al . Occluded building height estimation from single HR SAR image based on an iterative model matching technique [J]. Journal on Communications , 2013 , 34 ( 3 ): 68 - 75 . (in Chinese)

杨学志 , 叶铭 , 周芳 , 等 . 采用混合特征相似性的极化SAR图像降噪算法 [J]. 电子学报 , 2016 , 44 ( 11 ): 2583 - 2591 .

YANG Xue-zhi , YE Ming , ZHOU Fang , et al . Speckle reduction for PolSAR images using hybrid features similarity [J]. Acta Electronica Sinica , 2016 , 44 ( 11 ): 2583 - 2591 . (in Chinese)

LEE J S . Speckle analysis and smoothing of synthetic aperture radar images [J]. Computer Graphics and Image Processing , 1981 , 17 ( 1 ): 24 - 32 .

KUAN T , SAWCHUK A A , STRAND T C , et al . Adaptive noise smoothing filter for images with signal-dependent noise [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence , 1985 , 7 ( 2 ): 165 - 177 .

FROST V S , STILES J A . A model for radar images and its application to adaptive digital filtering of multiplicative noise [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence , 1982 , 4 ( 2 ): 157 - 166 .

LOPES A , NEZRY E , TOUZI R , et al . Maximum a posteriori speckle filtering and first order texture models in SAR images [A]. International Geoscience and Remote Sensing Symposium [C]. Washington DC, USA : IEEE , 1990 . 2409 - 2412 .

LEE J S . Refined filtering of image noise using local statistics [J]. Computer Graphics and Image Processing , 1981 , 15 ( 14 ): 380 - 389 .

LOPES A , TOUZI R , NEZRY E . Adaptive speckle filters and scene heterogeneity [J]. IEEE Transactions on Geoscience and Remote Sensing , 1990 , 28 ( 6 ): 992 - 1000 .

YU Y , ACTON S . Speckle reducing anisotropic diffusion [J]. IEEE Transactions on Image Processing , 2002 , 11 ( 11 ): 1260 - 1270 .

张良培 , 王毅 , 李平湘 . 基于各向异性扩散的SAR图像斑点噪声滤波算法 [J]. 电子学报 , 2006 , 34 ( 12 ): 2250 - 2254 .

ZHANG Liang-pei , WANG Yi , LI Ping-xiang . The filtering algorithm for SAR image speckle noise based on anisotropic diffusion [J]. Acta Electronica Sinica , 2006 , 34 ( 12 ): 2250 - 2254 . (in Chinese)

LI H C , FAN P Z , KHAN M K . Context-adaptive anisotropic diffusion for image denoising [J]. Electronics Letters , 2012 , 48 ( 14 ): 827 - 829 .

朱磊 , 韩天琪 , 水鹏朗 , 等 . 一种抑制合成孔径雷达图像相干斑的各向异性扩散滤波方法 [J]. 物理学报 , 2014 , 63 ( 17 ): 179502-1 - 179502 - 11 .

ZHU Lei , HAN Tian-qi , SHUI Peng-lang , et al . An anisotropic diffusion filtering method for speckle reduction of synthetic aperture radar images [J]. Acta Physica Sinica , 2014 , 63 ( 17 ): 179502-1 - 179502 - 11 . (in Chinese)

SUMAIYA M N , KUMARI R S S . SAR image despeckling using heavy-tailed Burr distribution [J]. Signal , Image Video Processing, 2016 , 11 ( 1 ): 49 - 55 .

CUI H , YAN G , SONG H . A novel curvelet thresholding denoising method based on chi-squared distribution [J]. Signal , Image Video Processing, 2015 , 9 ( 2 ): 491 - 498 .

TIAN X , JIAO L , ZHANG X . Despeckling SAR images based on a new probabilistic model in nonsubsampled contourlet transform domain [J]. Signal , Image Video Processing, 2014 , 8 ( 8 ): 1459 - 1474 .

BUADES A , COLL B , MOREL J . A non-local algorithm for image denoising [J]. Computer Vision and Pattern Recognition , 2005 , 2 ( 7 ): 60 - 65 .

DABOV K , FOI A , KATKOVNIK V , et al . Image restoration by sparse 3D transform-domain collaborative filtering [J]. Browse Journals and Magazines , 2007 , 16 ( 8 ): 2080 - 2095 .

KERVRANN C , BOULANGER J , COUPE P . Bayesian non-local means filter , image redundancy and adaptive dictionaries for noise removal[A]. International Conference on Scale Space and Variational Methods in Computer Vision [C]. Berlin, Germany : Springer Berlin Heidelberg , 2007 . 520 - 532 .

ZHONG H , LI Y W , JIAO L C . Bayesian nonlocal means filter for SAR image despeckling [A]. Asia-Pacific Conference on Synthetic Aperture Radar [C]. Xi'an, China : IEEE , 2009 . 1096 - 1099 .

DELEDALLE C A , DENIS L , TUPIN F . Iterative weighted maximum likelihood denoising with probabilistic patch-based weights [J]. IEEE Transactions on Image Processing , 2009 , 18 ( 12 ): 2661 - 2672 .

CHEN S B , HOU J H , ZHANG H , et al . De-speckling method based on non-local means and coefficient variation of SAR image [J]. Electronics Letters , 2014 , 50 ( 18 ): 1314 - 1316 .

MARTINO G D , SIMONE A D , IODICE A , et al . Scattering-based nonlocal means SAR despeckling [J]. IEEE Transactions on Geoscience and Remote Sensing , 2016 , 54 ( 6 ): 3574 - 3588 .

陈世媛 , 李小将 . 基于自适应非局部均值的SAR图像相干斑抑制 [J]. 系统工程与电子技术 , 2017 , 39 ( 12 ): 2683 - 2690 .

CHEN Shi-yuan , LI Xiao-jiang . SAR image despeckling based on adaptive non-local means [J]. Systems Engineering and Electronics , 2017 , 39 ( 12 ): 2683 - 2690 . (in Chinese)

OLSHAUSEN B A , FIELD D J . Emergence of simple-cell receptive field properties by learning a sparse code for natural images [J]. Nature , 1996 , 381 ( 6583 ): 607 - 609 .

江金龙 , 孙洪 , 陈嘉宇 , 等 . SAR图像的Gamma混合分布建模方法 [J]. 信号处理 , 2014 , 30 ( 5 ): 504 - 510 .

JIANG Jin-long , SUN Hong , CHEN Jia-yu , et al . Gamma mixture distribution modeling method with SAR image [J]. Journal of Signal Processing , 2014 , 30 ( 5 ): 504 - 510 . (in Chinese)

DEMPSTER A P , LAIRD N M , RUBIN D B . Maximum likelihood from incomplete data via the EM algorithm [J]. Journal of Royal Statistical Society(Series B) , 1977 , 39 ( 1 ): 1 - 38 .

赵泉华 , 石雪 , 王玉 , 等 . 可变类空间约束高斯混合模型遥感图像分割 [J]. 通信学报 , 2017 , 38 ( 2 ): 34 - 43 .

ZHAO Quan-hua , SHI Xue , WANG Yu , et al . Remote sensing image segmentation based on spatially constrained Gaussian mixture model with unknown class number [J]. Journal on Communications , 2017 , 38 ( 2 ): 34 - 43 . (in Chinese)

王晓军 , 孙洪 , 管鲍 . SAR图像相干斑抑制滤波性能评价 [J]. 系统工程与电子技术 , 2004 , 26 ( 9 ): 1165 - 1183 .

WANG Xiao-jun , SUN Hong , GUAN Bao . Evaluation for coherent speckle suppression filters of SAR images [J]. Systems Engineering and Electronics , 2004 , 26 ( 9 ): 1165 - 1183 . (in Chinese)

薛存金 , 温晓阳 , 董庆 . SAR图像的自适应边缘保持去噪滤波 [J]. 应用科学学报 , 2011 , 29 ( 1 ): 44 - 50 .

XUE Cun-jin , WEN Xiao-yang , DONG Qing . Adaptive despeckling filter with edge-preservation for SAR image [J]. Journal of Applied Sciences-Electronics and Information Engineering , 2011 , 29 ( 1 ): 44 - 50 . (in Chinese)

PARRILLI S , PODERICO M , ANGELINO C V , et al . Nonlocal SAR image denoising algorithm based on LLMMSE wavelet shrinkage [J]. IEEE Transactions on Geoscience and Remote Sensing , 2012 , 50 ( 2 ): 606 - 616 .

FENG H , HOU B , GONG M . SAR image despeckling based on local homogeneous region segmentation by using pixel relativity measurement [J]. IEEE Transactions on Geoscience and Remote Sensing , 2011 , 49 ( 7 ): 2724 - 2737 .

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