Image Interpolation Based on Spiking Neural Network Model

dc.authorid0000-0002-1016-1655
dc.contributor.authorIncetas, Mursel Ozan
dc.date.accessioned2026-01-24T12:29:28Z
dc.date.available2026-01-24T12:29:28Z
dc.date.issued2023
dc.departmentAlanya Alaaddin Keykubat Üniversitesi
dc.description.abstractImage interpolation is used in many areas of image processing. It is seen that many techniques developed to date have been successful in both protecting edges and increasing image quality. However, these techniques generally detect edges with gradient-based linear calculations. In this study, spiking neural networks (SNNs), which are known to successfully simulate the human visual system (HVS), are used to detect edge pixels instead of the gradient. With the help of the proposed SNN-based model, the pixels marked as edges are interpolated with a 1D directional filter. For the remaining pixels, the standard bicubic interpolation technique is used. Additionally, the success of the proposed method is compared to known methods using various metrics. The experimental results show that the proposed method is more successful than the other methods.
dc.identifier.doi10.3390/app13042438
dc.identifier.issn2076-3417
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85149267342
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.3390/app13042438
dc.identifier.urihttps://hdl.handle.net/20.500.12868/5397
dc.identifier.volume13
dc.identifier.wosWOS:000938171100001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherMdpi
dc.relation.ispartofApplied Sciences-Basel
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WoS_20260121
dc.subjectimage interpolation
dc.subjectspiking neural network
dc.subjectedge detection
dc.titleImage Interpolation Based on Spiking Neural Network Model
dc.typeArticle

Dosyalar