New Point Matching Algorithm Using Sparse Representation of Image Patch Feature for SAR Image Registration
Image registration is an important preprocessing step in many synthetic aperture radar (SAR) image applications. A key issue in image registration is to reliably establish the correspondences between the feature points extracted from the reference and sensed images. A new point matching algorithm is...
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Veröffentlicht in: | IEEE transactions on geoscience and remote sensing 2017-03, Vol.55 (3), p.1498-1510 |
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creator | Fan, Jianwei Wu, Yan Wang, Fan Zhang, Peng Li, Ming |
description | Image registration is an important preprocessing step in many synthetic aperture radar (SAR) image applications. A key issue in image registration is to reliably establish the correspondences between the feature points extracted from the reference and sensed images. A new point matching algorithm is proposed in this paper to align two SAR images. In the proposed method, by considering image patches as the basic units, a novel local descriptor including the intensity and geometric information is assigned to each feature point, which is more robust to speckle noise. Furthermore, a correspondence establishment scheme is introduced based on the reconstruction errors between feature points calculated by the sparse representation (SR) technique, which is designed for achieving accurate matches. Based on the obtained SR coefficients, a coordinate correction procedure is further proposed for improving the localization accuracy of the obtained correspondences. Both simulated deformed and real SAR images are utilized to evaluate the performance. The experimental results indicate that the proposed method yields a better registration performance in terms of both accuracy and robustness. |
doi_str_mv | 10.1109/TGRS.2016.2626373 |
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A key issue in image registration is to reliably establish the correspondences between the feature points extracted from the reference and sensed images. A new point matching algorithm is proposed in this paper to align two SAR images. In the proposed method, by considering image patches as the basic units, a novel local descriptor including the intensity and geometric information is assigned to each feature point, which is more robust to speckle noise. Furthermore, a correspondence establishment scheme is introduced based on the reconstruction errors between feature points calculated by the sparse representation (SR) technique, which is designed for achieving accurate matches. Based on the obtained SR coefficients, a coordinate correction procedure is further proposed for improving the localization accuracy of the obtained correspondences. Both simulated deformed and real SAR images are utilized to evaluate the performance. The experimental results indicate that the proposed method yields a better registration performance in terms of both accuracy and robustness.</description><identifier>ISSN: 0196-2892</identifier><identifier>EISSN: 1558-0644</identifier><identifier>DOI: 10.1109/TGRS.2016.2626373</identifier><identifier>CODEN: IGRSD2</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Accuracy ; Algorithms ; Coefficients ; Computer simulation ; Deformation ; Fans ; Feature extraction ; Image patch ; Image reconstruction ; Image registration ; Localization ; Matching ; Mathematical analysis ; Methods ; point matching ; Radar imaging ; Registration ; Representations ; Robustness ; SAR (radar) ; sparse representation (SR) ; Speckle ; Synthetic aperture radar ; synthetic aperture radar (SAR) image</subject><ispartof>IEEE transactions on geoscience and remote sensing, 2017-03, Vol.55 (3), p.1498-1510</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2017</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c341t-951bfb1cabd563be030dd3c134be16f925b50db461d371d7619de8baec63dde83</citedby><cites>FETCH-LOGICAL-c341t-951bfb1cabd563be030dd3c134be16f925b50db461d371d7619de8baec63dde83</cites><orcidid>0000-0001-7502-2341 ; 0000-0002-8065-0948</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7763754$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/7763754$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Fan, Jianwei</creatorcontrib><creatorcontrib>Wu, Yan</creatorcontrib><creatorcontrib>Wang, Fan</creatorcontrib><creatorcontrib>Zhang, Peng</creatorcontrib><creatorcontrib>Li, Ming</creatorcontrib><title>New Point Matching Algorithm Using Sparse Representation of Image Patch Feature for SAR Image Registration</title><title>IEEE transactions on geoscience and remote sensing</title><addtitle>TGRS</addtitle><description>Image registration is an important preprocessing step in many synthetic aperture radar (SAR) image applications. A key issue in image registration is to reliably establish the correspondences between the feature points extracted from the reference and sensed images. A new point matching algorithm is proposed in this paper to align two SAR images. In the proposed method, by considering image patches as the basic units, a novel local descriptor including the intensity and geometric information is assigned to each feature point, which is more robust to speckle noise. Furthermore, a correspondence establishment scheme is introduced based on the reconstruction errors between feature points calculated by the sparse representation (SR) technique, which is designed for achieving accurate matches. Based on the obtained SR coefficients, a coordinate correction procedure is further proposed for improving the localization accuracy of the obtained correspondences. Both simulated deformed and real SAR images are utilized to evaluate the performance. The experimental results indicate that the proposed method yields a better registration performance in terms of both accuracy and robustness.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Coefficients</subject><subject>Computer simulation</subject><subject>Deformation</subject><subject>Fans</subject><subject>Feature extraction</subject><subject>Image patch</subject><subject>Image reconstruction</subject><subject>Image registration</subject><subject>Localization</subject><subject>Matching</subject><subject>Mathematical analysis</subject><subject>Methods</subject><subject>point matching</subject><subject>Radar imaging</subject><subject>Registration</subject><subject>Representations</subject><subject>Robustness</subject><subject>SAR (radar)</subject><subject>sparse representation (SR)</subject><subject>Speckle</subject><subject>Synthetic aperture radar</subject><subject>synthetic aperture radar (SAR) image</subject><issn>0196-2892</issn><issn>1558-0644</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kFFPwjAQxxujiYh-AONLE5-HvbXr2CMhgiSoZMBz0623MQLbbEuM395NiE93l_v_7pIfIY_ARgAsednM0_UoZCBHoQwlj_kVGUAUjQMmhbgmAwaJDMJxEt6SO-f2jIGIIB6Q_Qd-01VT1Z6-a5_vqrqkk0PZ2MrvjnTr-nndauuQpthadFh77aumpk1BF0ddIl31HJ2h9ieLtGgsXU_Syy7FsnLe_hH35KbQB4cPlzok29nrZvoWLD_ni-lkGeRcgA-SCLIig1xnJpI8Q8aZMTwHLjIEWSRhlEXMZEKC4TGYWEJicJxpzCU3XceH5Pl8t7XN1wmdV_vmZOvupQohFoLJsUy6FJxTuW2cs1io1lZHbX8UMNUrVb1S1StVF6Ud83RmKkT8z8dxt4wE_wUSCHM9</recordid><startdate>201703</startdate><enddate>201703</enddate><creator>Fan, Jianwei</creator><creator>Wu, Yan</creator><creator>Wang, Fan</creator><creator>Zhang, Peng</creator><creator>Li, Ming</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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subjects | Accuracy Algorithms Coefficients Computer simulation Deformation Fans Feature extraction Image patch Image reconstruction Image registration Localization Matching Mathematical analysis Methods point matching Radar imaging Registration Representations Robustness SAR (radar) sparse representation (SR) Speckle Synthetic aperture radar synthetic aperture radar (SAR) image |
title | New Point Matching Algorithm Using Sparse Representation of Image Patch Feature for SAR Image Registration |
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