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A neural network based transcoder for MPEG2 video compression

dc.citation.epage1128en_US
dc.citation.spage1125en_US
dc.contributor.authorFu, HCen_US
dc.contributor.authorChen, ZHen_US
dc.contributor.authorXu, YYen_US
dc.contributor.authorWang, CHen_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.date.accessioned2014-12-08T15:27:08Z
dc.date.available2014-12-08T15:27:08Z
dc.date.issued1999en_US
dc.description.abstractIn this paper, we proposed a neural network method for the high efficiency requatization in the design of a transcoder In our design, there are two types of video bitrate control in the proposed transcoder. One is the global adjusting of quantizer scales in which the adjusting is based on the complication of the whole frame, the other is the adaptive adjusting of quantizer scales, that the adjusting is the complication of the current macroblock. From our experimental results, the prototype transcoder can achieve desirable bitrate (1.5 Mbps) with an acceptable image quality. In additional, we constructed a video multiplexer for PPV or NVOD applications on the proposed transcoder.en_US
dc.identifier.isbn0-7803-5041-3en_US
dc.identifier.issn1520-6149en_US
dc.identifier.journalICASSP '99: 1999 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, PROCEEDINGS VOLS I-VIen_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/19371
dc.identifier.wosnumberWOS:000079690700282
dc.language.isoen_USen_US
dc.titleA neural network based transcoder for MPEG2 video compressionen_US
dc.typeProceedings Paperen_US

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