簡易檢索 / 詳目顯示

研究生: 周郁玲
Chou, Yu-Lin
論文名稱: Complexity Modeling and Applications of H.264/SVC Decoding
可調式視訊編碼之解碼複雜度塑模及應用
指導教授: 林嘉文
Lin, Chia-Wen
口試委員: 彭文孝
Peng, Wen-Hsiao
陳永昌
Chen, Yung-Chang
王昱舜
Wang, Yu-Shuen
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 電機工程學系
Department of Electrical Engineering
論文出版年: 2012
畢業學年度: 100
語文別: 中文
論文頁數: 49
中文關鍵詞: 可調式視訊編碼複雜度估測
外文關鍵詞: Scalable Video Coding, Complexity prediction
相關次數: 點閱:3下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • In recent years, along with the rapid development of network infrastructures and storage capacity, multimedia resources are explosively growing in our daily lives. Multimedia resources nowadays are easily accessible and their applications range from many areas, like multimedia messaging, video telephony and video conferencing. Users nowadays can use the video-content application on heterogeneous devices, such as PC, smart phone and TVs. With some many different devices, the issue of how to adapt video on different personal devices will become more and more important in the future.
    Scalable Video Coding is an extension of H.264 and is the latest video coding standard proposed by ITU-T and ISO/IEC. It provides an attractive solution to the problems posed by modern requirement of heterogeneous devices. The scalability functions help to remove the video redundancy parts, and are fit to different user’s requirement. The objective of SVC standardization is to encode the high –quality bitstream in one main bitstream and many other sub streams. Users can base on their capacity or preference to choose the needed bitstream. However, despite three scalabilities provided in SVC, it still not solve all the requirements especially the power one which becomes more and more important in recent years. In our following work, we provide a model that can base on the bitstream content and personal devices’ characteristics adjusting the decoding complexity and then achieve the requirement of various power constraints.


    近年來隨著網路與硬體的技術越發進步,多媒體的資訊已爆炸性地速度在日常生活中增長。使人們今日要取得多媒體的資訊非常方便,相關的服務也因此非常多樣化,例如多媒體簡訊、視訊電話與視訊會議。今日用戶會利用不同的多媒體接取裝置,例如個人電腦、智慧型手機及電視等等,來收看多媒體相關的內容,因此如何調整資訊來配合不同的裝置上在未來將會是一個益發重要的話題。
    可調式視訊編碼是由ITU-T 和 ISO/IEC共同提出的最新視訊編碼標準。其可調式的編碼方式,提供上段敘述問題一個非常不錯的解決方式。在可調式視訊編碼中,編碼端會將高畫質的影片分別編成一個主要的基礎資訊流與許多分開的增強資訊流,因此在接收端,使用者可依照不同的需求,如手邊儀器的能力或個人喜好等,來選擇影片需要的部分。然而,雖然可調式視訊編碼已經提供許多(如 影片播放流暢度、大小與品質)的選擇,卻尚未提供解碼端一個可依解碼電力消耗適度做調整的選項,然而這個選擇功能,在目前廣泛被使用的手持式裝置尤其重要,因此在接下來的研究中,我們提出了一個與電力消耗相對應的運算複雜度估測方式,來依據接收端的能力與影片的內容,估測出不同影片在解碼所會造成的不同複雜度,使接收端在解碼前,即可得知不同影片的抽取所會消耗的解碼電力,以此來對應調整出最適合目前階段接收的影片資料量,以此來達到電力控制上的需求。

    摘 要 Abstract 目 錄 Chapter 1 Introduction 1.1 Scalable Video Coding (SVC) 1.2 Motivation 1.3 Objective 1.4 Thesis organization Chapter 2 Overview of Scalable Video Coding 2.1 Background of Scalable Video Coding 2.2 Major features in Scalable Video Coding 2.2.1 Temporal Scalability 2.2.2 Spatial and Quality Scalability Chapter 3 Video Decoding Complexity Model 3.1 Coding-based Complexity Model 3.1.1 MPEG-4 Decoding Complexity Model 3.1.2 H.264/AVC Decoding Complexity Model 3.2 Coding-based Complexity Model with Hardware Concern 3.2.1 Generic Decoding Complexity Model 3.2.2 H.264/AVC Decoding Complexity Model Chapter 4 The Proposed SVC Decoding Complexity Model and Its Application 4.1 Model Design and Illustration 4.1.1 The Decoding Complexity Model of SCP 4.1.2 The Decoding Complexity Model of MCP 4.1.3 The Decoding Complexity Model of Entropy Process 4.2 Formulation of the Decoding Complexity Model 4.2.1 Training Process 4.2.2 Least-squares method 4.3 Application of the SVC Decoding Complexity Model Chapter 5 Experiments and Discussion 5.1 Experiment environment 5.2 Proposed SVC complexity model 5.2.1 Base layer 5.2.2 Temporal scalability 5.2.3 Quality scalability 5.2.4 Spatial scalability 5.3 The Application of the SVC Bitstream’s Optimal Extraction Chapter 6 Conclusion and Future Work References Appendix

    [1]H.264 SVC Reference Software (JSVM 9.15) and Manual CVS sever, JVT, Sep. 2008 [Online]. Available: garon.ient.rwth-aachen.de.
    [2]Information Technology-Coding of Audio Objects-Part 2 : Visual,ISO/IEC JCT1/SC29/WG11/N3930.
    [3]M. Mattavelli and S. Brunetton, “Implementing real-time video decoding on multimedia processors by complexity prediction techniques”, IEEE Trans. Consumer Electron, vol. 44, no. 3, pp. 760-767, Aug. 1998.
    [4]J. Valentim, P. Nunes, and F. Pereia, “Evluating MPEG-4 video decoding complexity for alternative video complexity verifier model,” IEEE Trans. Circuits Syst. Video Technol., vol. 12, no. 11, pp.1034-1044, Nov. 2002.
    [5]M. van der Schaar and Y. Andreopoulos, “Rate-distortion-complexity modeling for network and receiver aware adaption,” IEEE Trans. Multimedia, vol. 7, no. 3, pp. 471-479, Jun. 2005
    [6]Y. Andreopoulos and M. van der Schaar, “Complexity-constrained video bitstream shaping,” IEEE Trans. Signal Process., vol. 55, no. 5, pp.1967-1974, May 2007.
    [7]Y. Wang and S. F. Chang, “Complexity adaptive H.264 encoding for light weight stream,” in Proc. IEEE Int, Conf. Acoust. Speech Signal Process. (ICASSP), May 2006, pp. II25-II28.
    [8]H.Schwarz, T.Hinz, D.Marpe, and T. Wiegand, “Constrained inter-layer prediction for single-loop decoding in spatial scalability”, in IEEE Int. Conf. on Img. Process (ICIP),Sep. 2005, p. II-870-3.
    [9]H.Schwarz, D.Marpe, and T. Wiegand, “Further results on constrained inter-layer prediction (JVT-O074), ” in JVT Meeting (Joint Video Team of ISO/IEC MPEG & ITU-T VCEG), Busan, Korea, April. 16-22,2005.
    [10]S.-W. Lee and C.-C. J. Kuo, “Complexity Modeling of Spatial and Temporal Compensations in H.264/AVC Decoding”, Circuits and Systems for Video Technology, IEEE Transactions, volume 20, No.5, pp. 706-720, May. 2010.
    [11]S.-W. Lee and C.-C. J. Kuo, “H.264/AVC entropy decoder complexity analysis and its applications”, Journal of Visual Communication and Image Representation, vol. 22, no. 1, pp. 61–72, Jan. 2011.

    無法下載圖示 全文公開日期 本全文未授權公開 (校內網路)
    全文公開日期 本全文未授權公開 (校外網路)

    QR CODE