DC Field | Value | Language |
---|---|---|
dc.contributor.author | KIM, KYUNG TAE | - |
dc.contributor.author | Jae-Ho Choi | - |
dc.contributor.author | Myung-Jun Lee | - |
dc.contributor.author | Nam-Hoon Jeong | - |
dc.contributor.author | Geon Lee | - |
dc.date.accessioned | 2023-03-03T05:20:57Z | - |
dc.date.available | 2023-03-03T05:20:57Z | - |
dc.date.created | 2023-03-03 | - |
dc.date.issued | 2022-04 | - |
dc.identifier.issn | 0196-2892 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/116584 | - |
dc.description.abstract | Synthetic aperture radar (SAR) systems, which operate under a slant-viewing geometry, inevitably entail shadow regions in the resulting radar image. Such shadow profiles contain backprojected signatures of an object's configuration as with target profiles; however, they are rarely utilized in current SAR-based recognition techniques. A major challenge in leveraging shadow information together lies in the intrinsic limitation of current single-pathway approaches, in which the target and shadow cannot be addressed simultaneously because of their incompatible domain properties. Hence, we herein propose novel solutions that enable the successful fusion of target and shadow regions within SAR for the first time. First, we devise new image preprocessing techniques specifically customized for shadows to compensate for their unique domain characteristics, which are distinct from the target. Second, we introduce a parallelized SAR processing mechanism such that a network can independently extract features oriented toward each conflicting modality. Third, adaptive fusion strategies are proposed for the optimal integration of features from each region while considering their relative significance layer by layer. Extensive experiments on public benchmark datasets demonstrate that the proposed framework allows a network to effectively employ shadow signatures and targets, thereby outperforming previous methods significantly for all setups. © 2022 IEEE. | - |
dc.language | English | - |
dc.publisher | Institute of Electrical and Electronics Engineers | - |
dc.relation.isPartOf | IEEE Transactions on Geoscience and Remote Sensing | - |
dc.title | Fusion of Target and Shadow Regions for Improved SAR ATR | - |
dc.type | Article | - |
dc.identifier.doi | 10.1109/TGRS.2022.3165849 | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | IEEE Transactions on Geoscience and Remote Sensing, v.60 | - |
dc.identifier.wosid | 000794217400012 | - |
dc.citation.title | IEEE Transactions on Geoscience and Remote Sensing | - |
dc.citation.volume | 60 | - |
dc.contributor.affiliatedAuthor | KIM, KYUNG TAE | - |
dc.identifier.scopusid | 2-s2.0-85128320861 | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.type.docType | Article | - |
dc.subject.keywordPlus | CONVOLUTIONAL NEURAL-NETWORK | - |
dc.subject.keywordPlus | RECOGNITION | - |
dc.subject.keywordPlus | CLASSIFICATION | - |
dc.subject.keywordPlus | SEGMENTATION | - |
dc.subject.keywordPlus | SENSOR | - |
dc.subject.keywordPlus | SIGNAL | - |
dc.subject.keywordAuthor | Synthetic aperture radar | - |
dc.subject.keywordAuthor | Feature extraction | - |
dc.subject.keywordAuthor | Radar polarimetry | - |
dc.subject.keywordAuthor | Target recognition | - |
dc.subject.keywordAuthor | Clutter | - |
dc.subject.keywordAuthor | Radar imaging | - |
dc.subject.keywordAuthor | Training | - |
dc.subject.keywordAuthor | Attention mechanism | - |
dc.subject.keywordAuthor | automatic target recognition (ATR) | - |
dc.subject.keywordAuthor | feature-level fusion | - |
dc.subject.keywordAuthor | information fusion of target and shadow (IFTS) | - |
dc.subject.keywordAuthor | synthetic aperture radar (SAR) | - |
dc.relation.journalWebOfScienceCategory | Geochemistry & Geophysics | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Remote Sensing | - |
dc.relation.journalWebOfScienceCategory | Imaging Science & Photographic Technology | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Geochemistry & Geophysics | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Remote Sensing | - |
dc.relation.journalResearchArea | Imaging Science & Photographic Technology | - |
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