從H.264/AVC到具雙向階層式預測之SVC的時間視訊轉碼

碩士 === 國立清華大學 === 電機工程學系 === 99 === The scalable extension (SVC) of H.264/AVC uses a notion of layers within the encoded bitstream for providing temporal, spatial and quality scalability, separately or combined. This scalability allows adaptation depending on the scenarios with different devices...

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Bibliographic Details
Main Authors: Huang, Yen-Chieh, 黃彥傑
Other Authors: Lin, Chia-Wen
Format: Others
Language:en_US
Published: 2011
Online Access:http://ndltd.ncl.edu.tw/handle/44675793471745122133
Description
Summary:碩士 === 國立清華大學 === 電機工程學系 === 99 === The scalable extension (SVC) of H.264/AVC uses a notion of layers within the encoded bitstream for providing temporal, spatial and quality scalability, separately or combined. This scalability allows adaptation depending on the scenarios with different devices and heterogeneous networks. The SVC design requires scalability to be provided at the encoder side by exploiting inter-layer dependencies during encoding. This implies that existing H.264/AVC content cannot benefit from the scalability tools in SVC due to the lack of intrinsic scalability provided in the bitstream at encoding time. Since a lot of technical and financial effort is currently being spent on the migration from MPEG-2 equipment to H.264/AVC, it is unlikely that a new migration to SVC will occur in the short term. Due to broadcaster and content distributors want to have scalable bitstreams at their disposal, efficient technique for migration of single-layer content to a scalable format are desirable. In this thesis, an approach for temporal transcoding from H.264/AVC to SVC with hierarchical bidirectional prediction is discussed. The input H.264/AVC bitstream is fully decoded by the transcoder. Macroblock coding mode and motion vectors are extracted from the input and adjusted to encode the output bitstream. The mode decision algorithm is proposed to reduce the candidate coding modes and the motion vector decision algorithm is proposed to obtain the output motion vector based on the input motion vector. As a result, a significant decrease in computational complexity is achieved, while maintaining a close to optimum compression efficiency.