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DT-CWT와 인공 신경망을 이용한 영상 융합 방법
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | 한복규 | - |
| dc.contributor.author | 양현석 | - |
| dc.contributor.author | 이종민 | - |
| dc.contributor.author | 최병인 | - |
| dc.contributor.author | 양지현 | - |
| dc.contributor.author | 문영식 | - |
| dc.date.accessioned | 2021-06-22T13:23:11Z | - |
| dc.date.available | 2021-06-22T13:23:11Z | - |
| dc.date.created | 2021-02-18 | - |
| dc.date.issued | 2017-11 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/8517 | - |
| dc.description.abstract | In this paper, we propose an image fusion method using decomposed coefficients of DT-CWT and extracted hot-targets by artificial neural network. Experiential results show that the performance of our method has been improved in terms of the texture quality and the visibility of hot-targets. | - |
| dc.language | 한국어 | - |
| dc.language.iso | ko | - |
| dc.publisher | 대한전자공학회 | - |
| dc.title | DT-CWT와 인공 신경망을 이용한 영상 융합 방법 | - |
| dc.title.alternative | Image Fusion Method using DT-CWT and Artificial Neural Network | - |
| dc.type | Article | - |
| dc.contributor.affiliatedAuthor | 문영식 | - |
| dc.identifier.bibliographicCitation | 2017년 대한전자공학회 추계학술대회 논문집, pp.697 - 700 | - |
| dc.relation.isPartOf | 2017년 대한전자공학회 추계학술대회 논문집 | - |
| dc.citation.title | 2017년 대한전자공학회 추계학술대회 논문집 | - |
| dc.citation.startPage | 697 | - |
| dc.citation.endPage | 700 | - |
| dc.type.rims | ART | - |
| dc.description.journalClass | 3 | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | other | - |
| dc.identifier.url | https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE07276419 | - |
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