Fast transcoding algorithm from MPEG2 to H.264
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Donghyung | - |
dc.contributor.author | Jeong, Jechang | - |
dc.date.accessioned | 2022-12-21T09:39:38Z | - |
dc.date.available | 2022-12-21T09:39:38Z | - |
dc.date.created | 2022-09-16 | - |
dc.date.issued | 2006-12 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/180636 | - |
dc.description.abstract | Video transcoding is the process of converting a video from one format into another. A format is defined by characteristics such as bitrate, framerate, spatial resolution and coding syntax. In this paper, we present an algorithm for transcoding from MPEG2 to H.264 in the spatial domain. For fast transcoding, we exploit three kinds of information included in an MPEG2 bitstream, which are coded macroblock type, coded block pattern and motion vector. According to the coded macroblock type and coded block pattern, we adaptively select the macroblock mode during the H.264 encoding process. Furthermore, the motion vector is also reused when an inter16x16 mode is selected as a macroblock mode. Simulation results show that the proposed transcoder dramatically reduces total transcoding time at comparable PSNR. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Springer Verlag | - |
dc.title | Fast transcoding algorithm from MPEG2 to H.264 | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Jeong, Jechang | - |
dc.identifier.doi | 10.1007/11949534_107 | - |
dc.identifier.scopusid | 2-s2.0-42149156991 | - |
dc.identifier.bibliographicCitation | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.4319 LNCS, pp.1067 - 1074 | - |
dc.relation.isPartOf | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.citation.title | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.citation.volume | 4319 LNCS | - |
dc.citation.startPage | 1067 | - |
dc.citation.endPage | 1074 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | Artificial intelligence | - |
dc.subject.keywordPlus | Computer science | - |
dc.subject.keywordPlus | Computers | - |
dc.subject.keywordPlus | Coded block patterns | - |
dc.subject.keywordPlus | Encoding process | - |
dc.subject.keywordPlus | Macro block | - |
dc.subject.keywordPlus | Macroblock type | - |
dc.subject.keywordPlus | Motion Vectors | - |
dc.subject.keywordPlus | Spatial domains | - |
dc.subject.keywordPlus | Spatial resolution | - |
dc.subject.keywordPlus | Video-transcoding | - |
dc.subject.keywordPlus | Video signal processing | - |
dc.identifier.url | https://link.springer.com/chapter/10.1007/11949534_107 | - |
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