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西安工程大学电子信息学院,西安,710048
Online First:10 April 2018,
Published:2018
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A Non-Local Means Filtering Algorithm for Despeckling of SAR Images[J]. 2018, 52(4): 98-104.
A Non-Local Means Filtering Algorithm for Despeckling of SAR Images[J]. 2018, 52(4): 98-104. DOI: 10.7652/xjtuxb201804014.
为了加强对SAR图像乘性相干斑噪声的抑制
并在相干斑抑制的同时有效提升对边缘的保护性能
提出了一种以均值比与变差系数联合构建的非局部平均(NLM)滤波(MR-NLM)算法。首先以搜索窗内各像素与中心像素在相似窗中的局部均值比替代传统高斯加权欧氏距离
构建对乘性相干斑噪声具有恒虚警边缘检测的相似性测量参量; 然后以变差系数替代传统常系数
构建对同质区与边缘区具有较好检测能力的自适应衰减因子; 最后利用新构建的相似性测量参量和衰减因子联合形成负指数加权系数
实现对SAR图像的非局部加权滤波。实验结果表明:MR-NLM算法与多种传统算法相比
具有更好的抑斑图像视觉效果及相干斑抑制与边缘保护性能
其等效视数提高10%以上
边缘保持指数提高1%以上。
A new non-local means(NLM)filtering algorithm(MR-NLM)based on the mean ratio(MR)and the variation coefficient is proposed to reduce multiplicative speckle noise of SAR images and to improve the edge preservation performance effectively. First
the local MR of each pixel to the center pixel in a search window is estimated by the similarity window
and the similarity measure parameter with constant false-alarm edge detection for the multiplicative speckle noise is constructed by using the MR to replace the traditional Gaussian weighted Euclidean distance. Secondly
an adaptive decay factor with good performance in detecting homogeneous and edge regions is constructed by using the variation coefficient to replace the traditional constant coefficient. Finally
negative exponential weighted coefficients are formed by combining the newly constructed similarity measure parameter with the decay factor
and then used to realize the non-local weighted filtering for SAR images. Experimental results and comparisons with several traditional filtering algorithms show that the MR-NLM algorithm has better visual effect for despeckled SAR images
better speckle suppression and edge preservation performance
and that the equivalent number of looks increases by more than 10%
and the edge preservation index improves by more than 1%.
FELIX B, GERALDINE Q, THIMM Z, et al. Comparative analysis of edge detection techniques for SAR images [J]. European Journal of Remote Sensing, 2016, 49(1): 205-224.
MORANDEIRA N S, GRIMSON R, KANDUS P. Assessment of SAR speckle filters in the context of object-based image analysis [J]. Remote Sensing Letters, 2016, 7(2): 150-159.
LEE J S. Digital image enhancement and noise filtering by using local statistics [J]. IEEE Transactions on Pattern Analysis Machine Intelligence, 1980, 2(2): 165-168.
朱磊, 水鹏朗, 章为川, 等. 利用区域划分的合成孔径雷达图像相干斑抑制算法 [J]. 西安交通大学学报, 2012, 46(10): 83-88.
ZHU Lei, SHUI Penglang, ZHANG Weichuan, et al. A despeckling algorithm for synthetic aperture radar image using region subdivision [J]. Journal of Xi'an Jiaotong University, 2012, 46(10): 83-88.
杨学志, 叶铭, 吴克伟, 等. 结构保持的双边滤波极化SAR图像降噪 [J]. 电子与信息学报, 2015, 37(2): 268-275.
YANG Xuezhi, YE Ming, WU Kewei, et al. A despeckling algorithm for synthetic aperture radar image using region subdivision [J]. Journal of Electronics Information Technology, 2015, 37(2): 268-275.
YU Y, ACTON S. Speckle reducing anisotropic diffusion [J]. IEEE Transactions on Image Processing, 2002, 11(11): 1260-1270.
ZHU Lei, ZHAO Xiaotian, GU Meihua. SAR image despeckling using improved detail-preserving anisotropic diffusion [J]. Electronics Letters, 2014, 50(15): 1092-1093.
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 [J]. 物理学报, 2014, 63(17): 445-455.
ZHU Lei, HAN Tianqi, SHUI Penglang, et al. An anisotropic diffusion filtering method for speckle reduction of synthetic aperture radar images [J]. Acta Physica Sinica, 2014, 63(17): 445-455.
BHUIYANR M, AHMAD M, SWAMY M. Spatially adaptive wavelet-based method using the Cauchy prior for denoising the SAR images [J]. IEEE Transactions on Circuits and Systems for Video Technology, 2007, 17(4): 500-507.
XU Bin, CUI Yi, LI Zenghui, et al. Patch ordering based SAR image despeckling via transform-domain filtering [J]. IEEE Journal of Selected Topics in Applied Earth Observations Remote Sensing, 2015, 8(4): 1682-1695.
GAO Fei, XUE Xiangshang, SUN Jinping, et al. A SAR image despeckling method based on two-dimensional S transform shrinkage [J]. IEEE Transactions on Geoscience Remote Sensing, 2016, 54(5): 3025-3034.
BUADES A, COLL B, MOREL J M. A non-local algorithm for image denoising [C]∥ Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Piscataway, NJ, USA: IEEE, 2005: 60-65.
SARA P, MARIANA P, CESARIO V A, et al. A nonlocal SAR image denoising algorithm based on LLMMSE wavelet shrinkage [J]. IEEE Transactions on Geoscience Remote Sensing, 2012, 50(2): 606-616.
CHEN Shaobo, HOU Jianhua, ZHANG Hua, et al. De-speckling method based on non-local means and coefficient variation of SAR image [J]. Electronics Letters, 2014, 50(18): 1314-1316.
DELEDALLE C A, DENIS L, TUPIN F, et al. NL-SAR: A unified nonlocal framework for resolution preserving(pol)(in)SAR denoising [J]. IEEE Transactions on Geoscience Remote Sensing, 2015, 53(4): 2021-2038.
TOUZI R, LOPES A, BOUSQUET P. A statistical and geometrical edge detector for SAR images [J]. IEEE Transactions on Geoscience Remote Sensing, 1988, 26(6): 764-773.
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