可調式視訊編碼透過層際間(inter-layer)預測的技術，大幅改善編碼效能，但也大幅提高了計算複雜度。對於不同的視訊影片和編碼參數下，如何降低編碼的複雜度是增加可調式視訊編碼應用性的關鍵。本論文對於CGS可調性提出了一個以線上統計為基礎的快速模式決策演算法，包含為訓練階段和加速階段。在訓練階段，我們線上統計層際間的模式分佈、RD cost increase以及層際內RD cost increase關聯性以確保此統計能適應不同編碼設定下與不同視訊內容，並應用以此設計貝氏分類器和提早終止演算法以達成快速模式決策。在加速階段，依據貝氏分類器之loss functions可減少候選modes的數量並排序候選modes，提早終止演算法則進一步減少測試modes的數量。實驗顯示，我們提出的加速演算法可以節省73%左右的編碼時間，如果只考慮加速階段，則最多可節省78%左右的編碼時間，並且在不同的量化參數(QP)與影片內容時皆下幾乎不會造成PSNR的下降及位元率(bitrate)的上升。

Duo to the high coding complexity of scalable video coding (SVC) that tests all candidate modes in RD optimization (RDO), in this thesis, we propose an on-line statistics based fast mode decision algorithm for SVC with CGS scalability. This algorithm consists of a training stage and an acceleration stage. At the training stage, the encoder gets the correlations of inter-layer mode distributions and intra and inter-layer RD cost increases. By this, we not only consider the probability distribution functions of optimal modes but also take the RD cost increase that caused by selecting a non-optimal mode into account. At the acceleration stage, the Bayesian classifier and an early termination algorithm are applied to reduce the candidate modes in RDO. By online statistics, the encoder can change the decision rule to reduce the RD performance loss for different sequences and QP sets. The experimental results show that our proposed algorithm can speed up to 73%. At the acceleration stage, our proposed algorithm can speed up to 78% with negligible RD performance loss.

[1] T. Wiegand, G. Sullivan, and A. Luthra, “Draft ITU-T Recommendation and Final Draft International Standard of Joint Video Specification (ITU-T Rec. H.264 | ISO/IEC 14496-10 AVC),” ISO/IEC JTC1/SC29/WG11 and ITU-T SG16 Q.6, JVT-G050r1, 2003.
[2] T. Wiegand, G. Sullivan, J .Reichel, H. Schwarz, and M. Wien, “ Joint Draft 10 of SVC Amendment,” ISO/IEC JTC1/SC29/WG11 and ITU-T SG16 Q.6, JVT-W201, 2007.
[3] H. Schwarz, D. Marpe, and T. Wiegand, “Overview of the scalable video coding extension of the H.264/AVC standard,” IEEE Trans. Circuits Syst. Video Technol., vol. 17, no. 9, pp. 1103–1120, Sept. 2007.
[4] H.-C. Huang, W.-H. Peng, T. Chiang, and H.-M. Hang, “Advances in the scalable amendment of H.264/AVC,” IEEE communications Magazine, vol. 45, no. 1, pp. 68-77, Jan. 2007.
[5] H. Schwarz, D. Marpe, and T. Wiegand, “Hierarchical B pictures,” Joint Video Team, Doc. JVT-P074, Jul. 2005.
[6] M. Wien, H. Schwarz, amd T. Olbaum, “Performance analysis of SVC,” in Proceedings of IEEE International Conference on Multimedia and Expo, vol. 17, no. 9, pp. 1194-1203, Sept. 2007.
[7] H. Schwarz, D. Marpe, and T. Wiegand, “Analysis of hierarchical B-pictures and MCTF,” in Proceedings of Digital Object Identifier, pp. 1929-1932, 2006.
[8] Generic Coding of Moving Pictures and Associates Audio Information-Part 2: Video, ITU-T Rec. H.262 and ISO/IEC JTC 1, 2009.
[9] Video Coding for Low Bit Rate Communication, ITU-T Rec. H.263, ITU-T, Version 1: Nov. 1994, Version 2: Jan. 1998, Version 1: Nov. 2000.
[10] Coding of Audio-Video Objects-Part 2: Visual, ISO/IEC 14492-2 (MPEG-4 Visual), ISO/IEC JTC 1, Version 1: Apr. 1999, Version 2: Feb. 2000, Version 3: May 2004.
[11] Y.-D. Wu and C.-W. Tang, “The motion directed fast mode decision for spatial and CGS scalable video coding,” in Proceedings of IEEE International Conference on Broadband Multimedia Systems and Broadcasting, Apr. 2008.
[12] H.-C. Lin, W.-H. Peng, and H.-M. Hang, “Low-complexity macroblock mode decision algorithm for combined CGS and temporal scalability,” document JVT-W029.doc, ISO/IEC JTC1/SC29/WG11 and ITU-T SG16 Q.6, San Jose, CA, Apr. 2007.
[13] H. Li, Z.-G. Li, and C. Wen, “Fast mode decision for coarse grain SNR scalable video coding,” in Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 2, pp. 545-548, 2006.
[14] H. Li, Z. G. Li, C. Wen, and S. Xie, “Fast mode decision for coarse granular scalability via switched candidate mode sets,” in Proceeding of IEEE International Conference on Multimedia and Expo, pp. 1323-1326, Jul. 2007.
[15] H. Li and Z. G. Li, “Fast mode decision algorithm for inter-frame coding in fully scalable video coding,” IEEE Trans. Circuits Syst. Video Techno., Vol. 16, No.7, pp. 889-895, July 2006.
[16] S.-T. Kim, K. Konda, C.-S. Park, C.-S. Cho, and S.-J. Ko, “ Fast mode decision algorithm for inter-layer coding in scalable video coding,” IEEE Trans. Consumer Electronics, vol. 55, no. 3, pp. 1572-1580, 2009.
[17] C.-H. Yeh, K.-J. Fan, M.-J. Chen, and G.-L. Li, “Fast mode decision algorithm for scalable video coding using Bayesian theorem detection and Markov process,” IEEE Trans. Circuits Syst. Video Technol., vol. 20, no. 4, Apr. 2010.
[18] J. Ren and N. Kehtarnavaz, “Fast adaptive early termination for mode selection in H.264 scalable video coding,” in Proceedings of IEEE International Conference on Image Processing, pp. 2464-2467, 2008.
[19] C.-S. Park, B.-K. Dan, H. Choi, and S.-J. Ko, “A statistical approach for fast mode decision in scalable video coding,” IEEE Trans. Circuits Syst. Video Technol., vol. 19,no. 12 , pp. 1915-1920, Dec. 2009.
[20] S.-W. Jung, S.-J. Beak, C. -S. Park, and S.-J. Ko, “ Fast mode decision using all zero block detection for fidelity and spatial scalable video coding,” IEEE Trans. Circuits Syst. Video Technol., vol. 20, no. 2, pp. 201-206, Feb. 2010.
[21] H.-C. Lin, W.-H. Peng, and H.-M. Hang, “Fast context-adaptive mode decision algorithm for scalable video coding with combined coarse-grain quality (CGS) and temporal scalability,” IEEE Trans. Circuits Syst. Video Technol., vol. 20, no. 5, pp. 732-748, May 2010.
[22] J. Reichel, H. Schwarz, and M. Wien, Joint Scalable Video Model JSVM- 9, document JVT-V202.doc, ISO/IEC JTC1/SC29/WG11 and ITU-T SG16 Q.6, Jan. 2007.