완전 복소 홀로그램 압축 성능 분석
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 서주연 | - |
dc.contributor.author | 고현석 | - |
dc.date.accessioned | 2023-07-05T05:37:08Z | - |
dc.date.available | 2023-07-05T05:37:08Z | - |
dc.date.issued | 2023-02 | - |
dc.identifier.issn | 2287-5026 | - |
dc.identifier.issn | 2288-159X | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/113059 | - |
dc.description.abstract | 3차원 공간 상에 영상을 재현해낼 수 있는 홀로그램 기술은 사용자에게 실제와 같은 시각 경험을 제공한다. 홀로그램은 자연 영상에 비해 일반적으로 큰 데이터 크기를 갖기 때문에, 홀로그램의 상용화를 위해서는 효율적인 압축 기술이 필수적이다. 하지만 전통적인 압축 방식은 자연 영상 부호화에 최적화 되어 있기 때문에 홀로그램 압축에 적합하지 않다. 본 논문은 기존 압축 코덱인 JPEG2000과 HEVC(High Efficiency Video Coding), 그리고 홀로그램의 특성을 고려한 압축 코덱인 Interfere와 딥러닝 기반의 압축 네트워크를 이용하여 JPEG Pleno Holography 표준에 따라 완전 복소 홀로그램(full-complex hologram)을 압축 및 복원 후 성능을 비교 분석한다. | - |
dc.description.abstract | Hologram technology can reproduce images in 3D space, providing users with a realistic visual experience. Since most holograms have a lager amount of information than general natural images, compression technology is essential for commercialization of holograms. However, the traditional compression method is not suitable for the characteristics of holograms. In this paper, the performance is analyzed through compression and reconstruction of a full-complex hologram according to the JPEG Pleno Holography standard. For compression, traditional compression codecs, JPEG2000 and HEVC(High Efficiency Video Coding), and Interfere and deep learning-based compression network considering the characteristics of the holograms are used. | - |
dc.format.extent | 15 | - |
dc.language | 한국어 | - |
dc.language.iso | KOR | - |
dc.publisher | 대한전자공학회 | - |
dc.title | 완전 복소 홀로그램 압축 성능 분석 | - |
dc.title.alternative | Compression Performance Analysis on Full-complex Hologram | - |
dc.type | Article | - |
dc.publisher.location | 대한민국 | - |
dc.identifier.doi | 10.5573/ieie.2023.60.2.79 | - |
dc.identifier.bibliographicCitation | 전자공학회논문지, v.60, no.2, pp 79 - 93 | - |
dc.citation.title | 전자공학회논문지 | - |
dc.citation.volume | 60 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 79 | - |
dc.citation.endPage | 93 | - |
dc.identifier.kciid | ART002931333 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | kci | - |
dc.subject.keywordAuthor | Computed-generated hologram(CGH) | - |
dc.subject.keywordAuthor | Full-complex hologram | - |
dc.subject.keywordAuthor | Hologram compression | - |
dc.subject.keywordAuthor | Deep learning-based compression | - |
dc.identifier.url | https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11218810 | - |
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