Please wait a minute...
img

官方微信

遥感技术与应用  2023, Vol. 38 Issue (5): 1118-1125    DOI: 10.11873/j.issn.1004-0323.2023.5.1118
数据与图像处理     
融合多方向Sobel算子的相干斑各向异性扩散抑制
张婧1(),郭风成1(),左泽丹2,丁鹏辰1,陈思帼1,孙闯1,刘文宋1
1.江苏师范大学 地理测绘与城乡规划学院,江苏 徐州 221116
2.苏州规划设计研究院股份有限公司徐州分公司,江苏 徐州 221112
Speckle Anisotropic Diffusion Suppression by Multidirectional Sobel
Jing ZHANG1(),Fengcheng GUO1(),Zedan ZUO2,Pengchen DING1,Siguo CHEN1,Chuang SUN1,Wensong LIU1
1.School of Geography,Geomatics and Planning,Jiangsu Normal University,Xuzhou 221116,China
2.Suzhou Planning and Design Research Institute Co. ,Ltd. Xuzhou Branch,Xuzhou 221112,China
 全文: PDF(2303 KB)   HTML
摘要:

相干斑的存在严重干扰了SAR图像质量,亟需对其抑制处理。传统AD(Anisotropic Diffusion)滤波器边缘检测模型精准度仍有提升空间,且噪声抑制效果往往受限于扩散阈值较难准确估计的问题。针对上述问题,提出了一种融合多方向Sobel算子的相干斑各向异性扩散抑制方法。该方法是SRAD(Speckle Reducing Anisotropic Diffusion)的改进算法,其利用多方向Sobel算子在SAR影像各点处构建了全新的边缘检测模型,并基于此,融合高斯核函数建立了新的AD扩散函数,可有效解决传统AD扩散系数受参数估计限制,提升了相干斑各向异性抑制的准确性。实验选取了3景真实SAR影像进行滤波实验,结果表明:该方法可有效提高边缘检测能力,获取更优相干斑抑制效果。

关键词: 相干斑噪声抑制各向异性扩散边缘检测多方向Sobel    
Abstract:

Speckle is an inherent property of SAR image, but its existence seriously interferes with the quality of SAR image and affects the high-quality application based on SAR image, so it is urgent to suppress it. The accuracy of the edge detection model of the traditional AD (Anisotropic Diffusion) filter still has room for improvement, and the noise suppression effect is often limited by the problem that it is difficult to accurately estimate the diffusion threshold. To solve the above problems, a novel AD filter based on Multidirectional Sobel (MSAD) is proposed. MSAD filter is an improved algorithm of SRAD. It builds a new edge detection model based on Multidirectional Sobel templates. Based on this, a new AD diffusion coefficient is established by integrating Gaussian kernel function, which can effectively solve the limitation of traditional AD diffusion coefficient by parameter estimation and improve the accuracy of speckle anisotropy suppression. Three real SAR images are selected for filtering experiments. In experiments, SRAD, DPAD, EnLee, and PPB filters are selected as the comparison algorithms; ENL, SSI, ESI, and M-Index are selected to evaluate the performance of proposed algorithms. Experiments show that MSAD filter can effectively improve the edge detection ability and obtain better speckle suppression effect.

Key words: Speckle    Noise suppression    Anisotropic diffusion    Edge detection    Multidirectional sobel
收稿日期: 2022-07-28 出版日期: 2023-11-07
ZTFLH:  P237  
基金资助: 国家自然科学基金项目(62101219);江苏省自然科学基金项目(BK20210921);江苏师范大学自然科学研究基金项目(20XSRS008)
通讯作者: 郭风成     E-mail: 739409323@qq.com;fchguo@jsnu.edu.cn
作者简介: 张 婧(2001-),女,江苏扬州人,本科生,主要从事SAR相干斑抑制研究。E?mail: 739409323@qq.com
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
张婧
郭风成
左泽丹
丁鹏辰
陈思帼
孙闯
刘文宋

引用本文:

张婧,郭风成,左泽丹,丁鹏辰,陈思帼,孙闯,刘文宋. 融合多方向Sobel算子的相干斑各向异性扩散抑制[J]. 遥感技术与应用, 2023, 38(5): 1118-1125.

Jing ZHANG,Fengcheng GUO,Zedan ZUO,Pengchen DING,Siguo CHEN,Chuang SUN,Wensong LIU. Speckle Anisotropic Diffusion Suppression by Multidirectional Sobel. Remote Sensing Technology and Application, 2023, 38(5): 1118-1125.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2023.5.1118        http://www.rsta.ac.cn/CN/Y2023/V38/I5/1118

图1  MS边缘检测模板
图2  滤波实验影像
图3  GF-3 SAR影像不同滤波器滤波结果。
图4  GF-3 SAR影像不同滤波器获取的比值影像
滤波方法ENLSSIESIM指标
未滤波2.77---
SRAD38.380.590.2415.89
DPAD17.500.800.3222.49
EnLee31.870.850.2116.53
PPB50.920.670.3114.03
MSAD32.000.540.315.82
表1  GF-3 SAR影像不同滤波器指标评价结果
图5  TerraSAR-X SAR影像不同滤波器滤波结果
图6  TerraSAR-X SAR影像不同滤波器获取的比值影像
滤波方法ENLSSIESIM指标
未滤波3.50---
SRAD97.150.650.1713.94
DPAD24.580.740.3011.89
EnLee61.380.670.1220.13
PPB138.500.630.2226.08
MSAD77.740.630.2410.97
表2  TerraSAR-X SAR影像不同滤波器指标评价结果
图7  RadarSAT-2 SAR影像不同滤波器滤波结果
图8  RadarSAT-2 SAR影像不同滤波器获取的比值影像
滤波方法ENLSSIESIM指标
未滤波12.19---
SRAD943.600.600.1832.71
DPAD301.170.740.20130.77
EnLee691.580.660.1036.88
PPB3 669.700.580.1631.18
MSAD865.310.560.2327.18
表3  RadarSAT-2 SAR影像不同滤波器指标评价结果
1 GUO Huadong, WU Wenjin, ZHANG Ke, et al. New SAR for earth observation[J]. Acta Geodaetica et Cartographica Sinica,2022,51(6):862-872.
1 郭华东,吴文瑾,张珂,等.新型SAR对地环境观测[J]. 测绘学报,2022,51(6):862-872.
2 WAN Ling, YOU Hongjian, CHENG Yuebing, et al. Research progress of synthetic aperture radar image segmentation [J]. Remote Sensing Technology and Application, 2018, 33(1):20-24.
2 万玲,尤红建,程跃兵,等.合成孔径雷达图像分割研究进展[J].遥感技术与应用, 2018,33(1):10-24.
3 JIN Yaqiu. Microwave remote sensing and its development in China[J]. Journal of Microwaves, 2020,36(1):1-6.
3 金亚秋.微波遥感及其在中国的发展[J]. 微波学报, 2020, 36(1):1-6.
4 GUO Fengcheng, ZHANG Guo, ZHANG Qingjun, et al. Fusion despeckling based on surface variation anisotropic diffusion filter and ratio image filter[J]. IEEE Transactions on Geoscience and Remote Sensing, 2020, 58(4): 2398-2411.
5 LEE J S, WEN J, AINSWORTH T L. Improved Sigma filter for speckle filtering of SAR imagery[J]. IEEE Transactions on Geoscience and Remote Sensing,2009,47(1):202-213.
6 KIM K I, BAHNG S I, CHOE R N. Despeckling method of ultrasound images using closed-form shrinkage function based on cauchy distribution in wavelet domain[J].International Journal of Wavelets, Multiresolution and Information Processing,2020,18(4):2050026. DOI:10.1142/S0219691320500265
doi: 10.1142/S0219691320500265
7 GUO F C, ZHUO C C, LIU W S, et al. Pixel difference function and local entropy-based speckle reducing anisotropic diffusion[J]. IEEE Transactions on Geoscience and Remote Sensing,2022,60:5229516. DOI:10.1109/TGRS.2022.3182886
doi: 10.1109/TGRS.2022.3182886
8 MA X S, WANG C, YIN Z X, et al. SAR image despeckling by noisy reference-based deep learning method[J]. Transactions on Geoscience and Remote Sensing, 2020, 58(12): 8807–8818.
9 ZHANG G, GUO F C, ZHANG Q J, et al. Speckle reduction by directional coherent anisotropic diffusion[J]. Remote Sensing, 2019, 11(23): 2768. DOI:10.3390/rs11232768
doi: 10.3390/rs11232768
10 LI Chunsheng, YU Ze, CHEN Jie. Overview of high-resolution spaceborne SAR imaging and image quality improvement methods[J]. Journal of Radars, 2019, 8(6) :717-731.
10 李春升, 于泽, 陈杰.高分辨率星载SAR成像与图像质量提升方法综述[J].雷达学报, 2019, 8(6) :717-731.
11 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.
12 PERONA P, MALIK J. Scale space and edge detection using anisotropic diffusion[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 1990, 12(7):629-639.
13 YU Y J, ACTON S T. Speckle reducing anisotropic diffusion[J]. IEEE Transactions on Image Processing, 2002, 11(11): 1260-1270.
14 AJA-FERNANDEZ S, ALBEROLA-LOPEZ C. On the estimation of the coefficient of variation for anisotropic diffusion speckle filtering[J]. IEEE Transactions on Image Processing, 2006, 15(9): 2694-2701.
15 RIYA, GUPTA B, LAMBA S S. An efficient anisotropic diffusion model for image denoising with edge preservation[J]. Computers and Mathematics with Applications, 2021, 93(4):106-119.
16 GOMEZ L, OSPINA R, FRERY A C. Unassisted quantitative evaluation of despeckling filters[J]. Remote Sensing, 2017, 9(4):389. DOI: 10.3390/rs9040
doi: 10.3390/rs9040
[1] 马慧云,李亚楠,吴晓京,冉印泽,鄢俊洁. H8/AHI卫星数据的夜间陆地雾自动检测[J]. 遥感技术与应用, 2022, 37(2): 408-415.
[2] 张宝华,周文涛,吕晓琪. 基于稀疏分解和改进MRF模型的SAR海冰图像分割方法[J]. 遥感技术与应用, 2017, 32(4): 709-713.
[3] 张静怡,雷 斌,刘团结. 一种新型的空域SAR图像相干斑抑制方法[J]. 遥感技术与应用, 2012, 27(4): 523-529.
[4] 蒋李兵 王壮. 基于置信区间与形态重构的自适应滑窗新方法[J]. 遥感技术与应用, 2011, (3): 0-0.
[5] 蒋李兵,王壮. 基于置信区间与形态重构的自适应滑窗新方法[J]. 遥感技术与应用, 2011, 26(3): 315-321.
[6] 唐艳红,郝燕玲,卢志忠. 基于小波变换的航海雷达图像噪声抑制方法[J]. 遥感技术与应用, 2009, 24(3): 370-373.
[7] 金晟业,陈圣波,金丽华,汪自军,车大为. 遥感图像边缘提取微分方法及其应用[J]. 遥感技术与应用, 2008, 23(6): 729-734.
[8] 何 敏,何秀凤. 基于小波域HMT模型InSAR干涉图噪声滤波研究[J]. 遥感技术与应用, 2007, 22(4): 531-535.