SAR Ship Detection Based on Gaussian Probability and Eigenvalue Analysis

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dc.contributor.authorHanbay, Kazim
dc.date.accessioned2026-04-04T13:33:23Z
dc.date.available2026-04-04T13:33:23Z
dc.date.issued2025
dc.departmentİnönü Üniversitesi
dc.description.abstractSynthetic Aperture Radar (SAR) images are frequently used because they provide optimal image quality in all weather conditions. Nevertheless, SAR ship detection has two difficulties. One is coherent speckle noise, which raises false alarms and confuses ships with similar objects. This letter proposes an efficient ship detector for low contrast, inshore and dense targets. First, to accurately eliminate the land areas and speckle noise, the hessian matrix and eigenvalues of the images were calculated. The largest eigenvalue information was given as input to the Gaussian function and the standard deviation and average images of the images were calculated. Then, the standard deviation and average images were combined with a probabilistic approach to obtain an image that highlights the ship regions. Morphological operations and connected component analysis were performed on this image. Experimental results showed that the proposed method provides both accurate and faster results.
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [123E344]
dc.description.sponsorshipThis work was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under Project 123E344.
dc.identifier.doi10.1109/LSP.2025.3571640
dc.identifier.endpage2218
dc.identifier.issn1070-9908
dc.identifier.issn1558-2361
dc.identifier.orcid0000-0003-1374-1417
dc.identifier.scopus2-s2.0-105005883337
dc.identifier.scopusqualityQ1
dc.identifier.startpage2214
dc.identifier.urihttps://doi.org/10.1109/LSP.2025.3571640
dc.identifier.urihttps://hdl.handle.net/11616/109129
dc.identifier.volume32
dc.identifier.wosWOS:001499502100003
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorHanbay, Kazim
dc.language.isoen
dc.publisherIeee-Inst Electrical Electronics Engineers Inc
dc.relation.ispartofIEEE Signal Processing Letters
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250329
dc.subjectMarine vehicles
dc.subjectRadar polarimetry
dc.subjectEigenvalues and eigenfunctions
dc.subjectStandards
dc.subjectSynthetic aperture radar
dc.subjectMeteorology
dc.subjectDeep learning
dc.subjectCoastlines
dc.subjectAccuracy
dc.subjectTraining
dc.subjectEigenvalues
dc.subjectGaussian probability
dc.subjectship detection
dc.subjectsynthetic aperture radar (SAR)
dc.titleSAR Ship Detection Based on Gaussian Probability and Eigenvalue Analysis
dc.typeArticle

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