以線上統計為基礎應用於CGS可調式編碼器之快速模式決策

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：73

、訪客IP：3.17.110.119

姓名

吳柏宗(Bo-Zong Wu) 查詢紙本館藏

畢業系所

通訊工程學系

論文名稱

以線上統計為基礎應用於CGS可調式編碼器之快速模式決策
(Online Statistics Based Fast Mode Decision for Scalable Video Coding with CGS)

相關論文

★ 應用於車內視訊之光線適應性視訊壓縮編碼器設計	★ 以粒子濾波法為基礎之改良式頭部追蹤系統
★ 應用於空間與CGS可調性視訊編碼器之快速模式決策演算法	★ 應用於人臉表情辨識之強健式主動外觀模型搜尋演算法
★ 結合Epipolar Geometry為基礎之視角間預測與快速畫面間預測方向決策之多視角視訊編碼	★ 基於改良式可信度傳遞於同質區域之立體視覺匹配演算法
★ 以階層式Boosting演算法為基礎之棒球軌跡辨識	★ 多視角視訊編碼之快速參考畫面方向決策
★ 適用於唇形辨識之改良式主動形狀模型匹配演算法	★ 以運動補償模型為基礎之移動式平台物件追蹤
★ 基於匹配代價之非對稱式立體匹配遮蔽偵測	★ 以動量為基礎之快速多視角視訊編碼模式決策
★ 應用於地點影像辨識之快速局部L-SVMs群體分類器	★ 以高品質合成視角為導向之快速深度視訊編碼模式決策
★ 以運動補償模型為基礎之移動式相機多物件追蹤	★ 基於匹配代價曲線特徵之遮蔽偵測之研究

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

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。

摘要(英)

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.

關鍵字(中)

★ 快速模式決策
★ 貝氏分類器
★ 線上統計
★ 可調式視訊編碼

關鍵字(英)

★ fast mode decision
★ Bayesian classifier
★ on-line statistic
★ scalable video coding

論文目次

摘要 i
Abstract ii
目錄 iv
圖目錄 vi
表目錄 viii
第一章緒論 1
1.1 前言 1
1.2 研究動機 2
1.3 研究方法 3
1.4 論文架構 3
第二章 H.264 可調式視訊編碼器介紹 4
2.1 可調式視訊編碼器介紹 4
2.2 可調式視訊編碼架構 5
2.2.1 時間可調性(Temporal Scalability ) 6
2.2.2 空間可調性(Temporal Scalability) 7
2.2.3 雜訊比可調性(SNR Scalability) 8
2.3 基礎層之編碼技術介紹 8
2.4 增進可調式視訊編碼效率之工具 10
2.4.1 層際間畫面內編碼預測(Inter-Layer Intra Prediction) 11
2.4.2 層際間運動向量預測(Inter-Layer Motion Prediction) 12
2.4.3 層際間殘餘資訊預測(Inter-Layer Residual Prediction) 12
2.5 總結 13
第三章可調式視訊編碼器之快速演算法現況 14
3.1快速運動估測演算法 14
3.2快速模式決策演算法 15
3.3 提早終止(Early Termination)模式決策演算法 17
3.4 總結 18
第四章本論文所出之快速巨集區塊模式演算法 19
4.1 以線上統計為基礎之快速巨集區塊模式決策演算法 19
4.2以貝氏分類器為基礎之快速巨集區塊模式決策 20
4.2.1 層際間巨集區塊之關聯性 20
4.2.2 層際內Block Mode分佈關聯性 31
4.2.3 層際內RD Cost Increase關聯性 32
4.2.4 應用貝氏分類器於快速模式決策 34
4.3提早終止巨集區塊模式決策演算法 36
4.3.1 層際間RD cost increase關聯性 36
4.3.2應用層際間RD cost increase於提早終止區塊模式決策演算法 38
第五章實驗結果 43
5.1 實驗環境與參數設定 43
5.2貝氏分類器之快速模式決策演算法 44
5.3結合貝氏分類器與提早終止之快速模式決策演算法 47
5.4 總結 53
第六章結論與未來展望 54
參考文獻 55
Publications 57

參考文獻

[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.

指導教授

唐之瑋(Chih-Wei Tang)

審核日期

2010-7-22

推文