隨著手持行動裝置的快速發展與網路頻寬的大幅提升，視訊編碼於生活中扮演著相當重要的角色，其中，訊源編碼與可調式轉碼為其主要的技術，而紋理複雜度一直以來被視為視訊編碼相當重要的參考資訊。本篇碩士論文利用紋理複雜度之資訊提出兩種方法於高效能視訊編碼技術中，以提高訊源編碼之編碼效能與可調式視訊轉碼之轉碼效率。在訊源編碼技術中，本論文提出一兩階層殘餘值預測方法，透過畫面內編碼的殘餘值來預測當前畫面的殘餘值，進一步減少殘餘值所需編碼的位元數；在可調式視訊轉碼技術中，本論文提出兩套快速決策機制包含提前終止機制與動態信賴區間之模式預測機制，利用兩套快速決策機制以減少不必要的模式選擇計算，大幅降低視訊轉碼所需的時間。從實驗結果可看出本論文提出之兩方法，能有效提升訊源編碼之效能與可調式轉碼之效率。

With the development of resolution of mobile devices and the growth of bandwidth of network transmission, the source coding and transcoding techniques play an important role in lives. Among video coding, texture complexity is one of the important information, and is generally used in the coding techniques. This thesis presents two methods via texture complexity in source coding and transcoding. In source coding, a novel two-layer residual prediction method (TRP) is proposed for High Efficiency Video Coding (HEVC) to improve the performance of inter prediction. The proposed TRP further predicts the redundant residual with reconstructed texture to enhance the coding performance of HEVC. In transcoding, a coding unit complexity-based unit prediction method (CUP) is proposed for Scalable High Efficiency Video Coding (SHVC) to save the encoding time in quality scalability. The proposed CUP predicts the coding unit and prediction unit by considering the decoding information of input stream. Experimental results show that the proposed methods outperform HEVC and SHVC by 3.40% and 77.83% in bitrate and encoding time reductions.

誌謝 iv
中文摘要 v
Abstract vi
Contents vii
List of Figures ix
List of Tables x
Chapter 1 Introduction 1
1.1 Overview to Video Coding 1
1.2 Motivation 3
1.3 Contributions 3
1.4 Organization 4
Chapter 2 Background Review 6
2.1 Video Coding Standard 7
2.1.1 Overview of HEVC 7
2.2 Quad-Tree Coding Structure 10
2.3 Texture Complexity 11
2.3.1 Coded Block Flag 11
2.3.2 Coding Unit Complexity 12
Chapter 3 Two-Layer Residual Prediction 16
3.1 Overview 16
3.2 Two-Layer Residual Prediction 18
3.2.1 Dictionary Construction 19
3.2.2 Residual Prediction 21
3.3 Experimental Results of HEVC 24
3.3.1 Peak Signal-to-Noise Ratio 25
3.3.2 BDBR and BDPSNR 26
3.3.3 Encoding Time 26
3.3.4 Experimental Results 26
Chapter 4 CUC-Based Unit Prediction for SHVC Quality Scalability 31
4.1 Overview 31
4.2 CUC-Based Unit Prediction 35
4.2.1 Early Termination 35
4.2.2 Adaptive Confidence Interval 45
4.3 Experimental Results of SHVC 48
4.3.1 Time Reduction 49
4.3.2 Mode Reuse 49
4.3.3 Experimental Results 51
Chapter 5 Conclusion and Future Directions 56
5.1 Conclusion 56
5.2 Future Directions 57
Reference 59
Publication List 61

[1] T. Wiegand, G. J. Sullivan, G. Bjontegaard, and A. Luthra, “Overview of the H.264/AVC video coding standard,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 13, no. 7, pp. 560-576, Jul. 2003.
[2] G. J. Sullivan, J.-R. Ohm, W.-J. Han, and T. Wiegand, “Overview of the high efficiency video coding (HEVC) standard,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 22, no. 12, pp. 1649-1668, Dec. 2012.
[3] J.-W. Kang, M. Gabbouj, and C.-C. Kuo, “Sparse/DCT (S/DCT) two-layered representation of prediction residuals for video coding,” IEEE Transactions on Image Processing, vol. 22, no. 7, pp. 2711-2722, Jul. 2013.
[4] C.-H. Yeh, T.-Y. Tseng, C.-W. Lee, and C.-Y. Lin, “Predictive texture synthesis-based intra coding scheme for advanced video coding,” IEEE Transactions on Multimedia, vol. 17, no. 9, pp. 1508-1514, Aug. 2015.
[5] C.-H. Yeh, C.-W. Lee, S.-J. Fan Jiang, Y.-H. Sung, and W.-J. Huang, “Second order residual prediction for HEVC inter coding,” in Proceedings of Asia-Pacific Signal and Information Processing Association Annual Summit and Conference 2014 (APSIPA 2014), Dec. 2014.
[6] G. J. Sullivan and T. Wiegand, “Rate-distortion optimization for video compression,” IEEE Signal Processing Magazine, vol. 15, no. 6, pp. 74-90, Nov. 1998.
[7] F. Bossen, “Common HM Test conditions and software reference configurations,” JCTVC, Geneva, Switzerland, technical report JCTVC-L1100, Jan. 2013.
[8] HEVC Reference Software HM15.0. (2014 Apr.) [Online]. Available: https://hevc.hhi.fraunhofer.de/trac/hevc/browser/branches/HM-15.0-dev
[9] G. Bjontegaard, “Calculation of average PSNR differences between RD-curves,” ITU-T, Austin, Texas, United States, technical report VCEG-M33, Apr. 2001.
[10] Y.-L. Lee and J. Lim, “Early termination of CU encoding to reduce HEVC complexity,” JCTVC, Torino, Italy, technical report JCTVC-F045, Jul. 2011.
[11] K. Choi, S.-H. Park, and E. S. Jang, “Coding tree pruning based CU early termination,” JCTVC, Torino, Italy, technical report JCTVC-F092, Jul. 2011.
[12] W.-Y. Tseng, “Improvement of coding efficiency and transmission quality for scalable video coding” Doctoral dissertation, Department of Electrical Engineering, National Sun Yat-sen University, Taiwan, Jan. 2015.
[13] SHVC Reference Software SHM6.0. (2014 Jul.) [Online]. Available: https://hevc.hhi.fraunhofer.de/trac/shvc/browser/SHVCSoftware/branches/SHM-6-dev