HistSegNet: Histogram Layered Segmentation Network for SAR Image-Based Flood Segmentation

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dc.contributor.authorTurkmenli, Ilter
dc.contributor.authorAptoula, Erchan
dc.contributor.authorKayabol, Koray
dc.date.accessioned2025-01-06T17:43:15Z
dc.date.available2025-01-06T17:43:15Z
dc.date.issued2024
dc.description.abstractFloods are one of the most common natural disasters, causing fatalities and severe economic and environmental impacts, directly affecting agriculture, urban infrastructure, and transportation networks. Hence, it is of utmost importance that flooded areas are efficiently and effectively identified in the aftermath. Synthetic aperture radar (SAR) images are invaluable to this end, since the amount of microwave energy reflected from water is less than that from land, due to its low surface roughness and lack of apparent texture. In this study, we explore the combination of histograms with deep neural networks for the purpose of flood mapping. The proposed histogram extraction layers, specifically designed for SAR content, are integrated into deep segmentation neural networks and are tested on two real SAR datasets. Experimental results have shown that histogram layers integrated into deep segmentation neural networks improve the performance up to 6% in terms of intersection over union (IoU) with a negligible increase in the number of learnable parameters. The code of the work will be available at https://github.com/ilterturkmenli/HistSegNet.
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [123R108]
dc.description.sponsorshipThis work was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under Project 123R108.
dc.identifier.doi10.1109/LGRS.2024.3450122
dc.identifier.issn1545-598X
dc.identifier.issn1558-0571
dc.identifier.scopus2-s2.0-85202721537
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1109/LGRS.2024.3450122
dc.identifier.urihttps://hdl.handle.net/20.500.14669/2567
dc.identifier.volume21
dc.identifier.wosWOS:001308225500009
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIEEE-Inst Electrical Electronics Engineers Inc
dc.relation.ispartofIeee Geoscience and Remote Sensing Letters
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectHistograms
dc.subjectImage segmentation
dc.subjectRadar polarimetry
dc.subjectFloods
dc.subjectSynthetic aperture radar
dc.subjectSentinel-1
dc.subjectKernel
dc.subjectFlood segmentation
dc.subjecthistogram layer
dc.subjectSentinel-1 (S1)
dc.subjectsynthetic aperture radar (SAR)
dc.titleHistSegNet: Histogram Layered Segmentation Network for SAR Image-Based Flood Segmentation
dc.typeArticle

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