Image deinterlacing using region-based back propagation artificial neural network
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Qian, Yurong | - |
dc.contributor.author | Wang, Jin | - |
dc.contributor.author | Jeon, Gwanggil | - |
dc.contributor.author | Jeong, Jechang | - |
dc.date.accessioned | 2022-07-16T09:14:17Z | - |
dc.date.available | 2022-07-16T09:14:17Z | - |
dc.date.created | 2021-05-12 | - |
dc.date.issued | 2013-07 | - |
dc.identifier.issn | 0091-3286 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/162421 | - |
dc.description.abstract | A back propagation artificial neural network (BP-ANN) has good self-learning, self-adaptation and generalization abilities, which we intend to use to interpolate an image. The interpolated pixels are classified into two regions, each region corresponding to one BP-ANN. In order to optimize the structure of the BP-ANN and the process of deinterlacing, three experiments were performed to test the architecture and parameters of region-based BP-ANN. The experimental results show that the proposed algorithm with an 8 - 16 - 1 structure provides the best balance between time consumption and visual quality. Compared to the other six advanced deinterlacing algorithms, our region-based BP-ANN method provides about an average of 0.14 to 0.64 dB higher peak signal-to-noise-ratio while maintaining high efficiency. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS | - |
dc.title | Image deinterlacing using region-based back propagation artificial neural network | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Jeong, Jechang | - |
dc.identifier.doi | 10.1117/1.OE.52.7.073107 | - |
dc.identifier.scopusid | 2-s2.0-84892748397 | - |
dc.identifier.wosid | 000322478600010 | - |
dc.identifier.bibliographicCitation | OPTICAL ENGINEERING, v.52, no.7 | - |
dc.relation.isPartOf | OPTICAL ENGINEERING | - |
dc.citation.title | OPTICAL ENGINEERING | - |
dc.citation.volume | 52 | - |
dc.citation.number | 7 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Optics | - |
dc.relation.journalWebOfScienceCategory | Optics | - |
dc.subject.keywordPlus | INTERPOLATION METHOD | - |
dc.subject.keywordPlus | Algorithms | - |
dc.subject.keywordPlus | Neural networks | - |
dc.subject.keywordAuthor | deinterlacing | - |
dc.subject.keywordAuthor | back propagation artificial neural network | - |
dc.subject.keywordAuthor | image format conversion | - |
dc.identifier.url | https://www.spiedigitallibrary.org/journals/optical-engineering/volume-52/issue-7/073107/Image-deinterlacing-using-region-based-back-propagation-artificial-neural-network/10.1117/1.OE.52.7.073107.short | - |
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