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MCS Filter: A Multichannel Structure-Aware Speckle Filter for SAR Images

文献类型：期刊论文

作者Saheya, B.1,6; Cai, Rui1,6; Zhao, Hongyu1,6; Gong, Maoguo2,3,4; Li, Xiaofeng5
刊名IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
出版日期2025
卷号63页码:14
关键词Information filters Radar polarimetry Vectors Oceans Filtering algorithms Wiener filters Speckle Synthetic aperture radar Filtering theory Correlation Speckle filter structure description matrix synthetic aperture radar (SAR) wishart distribution
ISSN号0196-2892
DOI10.1109/TGRS.2025.3572612
通讯作者Gong, Maoguo(gong@ieee.org) ; Li, Xiaofeng(xiaofeng.li@ieee.org)
英文摘要Synthetic aperture radar (SAR) is widely recognized as an effective tool for investigating oceanic processes, particularly internal wave dynamics, due to its ability to capture high-resolution imaging across diverse environmental conditions. However, speckle noise in SAR imagery poses significant challenges for accurately extracting critical parameters, such as wavefront characteristics and bright-dark distances, thereby hindering its application in detailed internal wave studies. To address this, a novel speckle filtering method is proposed, specifically designed to enhance the quality of SAR images capturing the feature of the internal wave. First, a structural description matrix with complex values is introduced to encode pixel value correlations and local spatial features, enabling improved representation of wave-related contextual information within the SAR data. Second, a similarity testing framework based on the Wishart distribution is developed to identify and aggregate structurally similar regions, ensuring robust noise suppression while preserving essential structural parameters. The proposed method strikes a balance between speckle noise reduction and structural preservation, making it adaptable to a variety of SAR datasets. Experimental validation on SAR imagery of oceanic internal waves demonstrates the method's effectiveness in retaining key internal wave information, while additional tests on terrestrial targets highlight its potential for generalization across different scenarios.
WOS关键词WISHART DISTRIBUTION ; NONLOCAL MEANS ; NOISE ; EFFICIENT
资助项目National Natural Science Foundation of China[62161044] ; National Natural Science Foundation of China[62161045] ; Natural Science Foundation of Inner Mongolia[2023MS06003] ; Natural Science Foundation of Inner Mongolia[2022ZD05] ; Key Laboratory of Infinite-Dimensional Hamiltonian System and Its Algorithm Application (IMNU), Ministry of Education[2023KFYB06] ; Research Program of Inner Mongolia Normal University[CXJJS25026]
WOS研究方向Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:001508119500010
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://ir.qdio.ac.cn/handle/337002/202280]  
专题海洋研究所_海洋环流与波动重点实验室
通讯作者Gong, Maoguo; Li, Xiaofeng
作者单位1.Inner Mongolia Normal Univ, Coll Math Sci, Ctr Appl Math Sci, Hohhot 010022, Peoples R China
2.Inner Mongolia Normal Univ, Acad Artificial Intelligence, Hohhot 010022, Peoples R China
3.Inner Mongolia Normal Univ, Coll Math Sci, Key Lab Infinite Dimens Hamiltonian Syst & Its Alg, Hohhot 010022, Peoples R China
4.Xidian Univ, Sch Elect Engn, Key Lab Collaborat Intelligence Syst, Minist Educ, Xian 710071, Peoples R China
5.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Observat & Forecasting, Key Lab Ocean Circulat & Waves, Qingdao 266071, Peoples R China
6.Inner Mongolia Normal Univ, Key Lab Infinite Dimens Hamiltonian Syst & Its Alg, Hohhot 010022, Peoples R China
推荐引用方式
GB/T 7714		 Saheya, B.,Cai, Rui,Zhao, Hongyu,et al. MCS Filter: A Multichannel Structure-Aware Speckle Filter for SAR Images[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2025,63:14.
APA Saheya, B.,Cai, Rui,Zhao, Hongyu,Gong, Maoguo,&Li, Xiaofeng.(2025).MCS Filter: A Multichannel Structure-Aware Speckle Filter for SAR Images.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,63,14.
MLA Saheya, B.,et al."MCS Filter: A Multichannel Structure-Aware Speckle Filter for SAR Images".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 63(2025):14.

入库方式： OAI收割

来源：海洋研究所

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