基於主觀視覺之H.264可調式視訊編碼空間層位元率分配機制

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紀珮茹(Pey-Ru Chi) 查詢紙本館藏

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通訊工程學系

論文名稱

基於主觀視覺之H.264可調式視訊編碼空間層位元率分配機制
(H.264/SVC Rate Allocation for Spatial Scalability Based on Perceptual Quality Metric)

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摘要(中)

H.264可調式視訊編碼是最新一代之可調適視訊編碼標準。其提供三種可調適架構包含時間可調性，空間可調性與品質可調性，同時滿足不同應用服務之需求。其中空間層可調性架構因其可同時提供不同解析度之視訊資料供使用者選擇而最廣泛的被應用。而在實際的應用層面上，如何有效率的分配位元率給不同解析度的空間層，是十分重要的議題。
現行的SVC編碼架構利用低解析度空間層資訊對高解析度層做編碼，因此低解析度空間層信號被視為最重要，因此編碼以維持最低解析度空間層的品質，即固定低解析度空間層量化參數繼而調整高解析度空間層畫面量化參數之方式來達到頻寬限制的要求。然而，根據實驗結果顯示人眼視覺系統對於高解析度畫面有較高的敏感度，因此位元率下降所造成的畫面失真影響在高解析度空間層，將更為嚴重。在頻寬共享的環境中，對不同解析度的使用者而言，應要能享有幾近相同的視訊服務品質。本論文即以在頻寬有限的條件下，分配位元率給不同解析度空間層，提供各個不同解析度需求使用者最佳之視訊品質。
本論文提出一套在網路資源有限的情況下，考量使用者主觀視覺感受的H.264可調式視訊編碼空間層位元率分配機制，改善傳統固定各層QP的位元率分配機制下，高解析視訊擁有較低的主觀視覺品質。我們降低人眼視覺中較不靈敏的低解析度視訊品質，並提升高解析度視訊品質，期望不同解析度的使用者（或當使用者變動使用距離時），能擁有接近的主觀視覺品質，實驗結果顯示，本論文所提的位元分配機制可有效率的分配位元率使各解析度空間層達到相近的主觀視覺品質，且對於不同視訊資料在不同的頻寬限制下均表現良好，更進一步提升了以主觀視覺品質為目標之下的頻寬使用率。

摘要(英)

H.264 scalable extension (SVC), which is constructed based on H.264/AVC, is the most recent scalable video coding standard. It offers three scalabilities in spatial, temporal, and quality, to meet multiple requirements simultaneously. Spatial scalability that can support multiple display resolutions with a wide range of bitrates is used widely. How to efficiently allocate a given total bitrate among multiple layers under the bandwidth constraint is an important issue and should be solved at first.
The base layer is usually treated more important than the enhancement layer because the information in base layer will often be re-used in enhancement layers. Therefore, under a bandwidth constraint, we usually run SVC by fixing the Qutization Parameter (QP) or the bitrate of the base layer while adaptively adjusting the ones of the enhancement layers. However, it is observed that Human Visual System (HVS) is more sensitive to higher resolution videos; in other words, the quality degradation at higher layers to human eyes would be more serious than that at lower layers. The main objective of this work is to achieve best and equal quality for each resolution layer under a given bandwidth constraint.
This thesis proposes a rate allocation method for SVC spatial scalability based on perceptual quality metric. We utilize the subjective metric, instead of conventional objective measurement PSNR, to measure video quality. Each resolution layer is measured by the quality metric and allocated with the corresponding rate to have similar quality. The disadvantage of the conventional fixed QP scheme that the higher resolution layer has worse subjective quality is improved. In simulations, several video sequences with various total rate constraints are experimented. The proposed method can efficiently allocate the rate for each layer with almost the same video quality in subjective measurement.

關鍵字(中)

★ Spatial Scalability
★ H.264 Scalable Video Coding
★ Perceptual Quality Metric
★ Rate Allocation

關鍵字(英)

★ 主觀視覺評量
★ 空間可調性
★ 位元率分配
★ H.264可調式視訊編碼

論文目次

摘要 I
ABSTRACT II
目錄 III
表目錄 V
圖目錄 VI
第一章緒論 1
1.2研究動機與目的 3
1.3論文架構 6
第二章視訊編碼器介紹 7
2.1 H.264單層視訊編碼器 7
2.1.1整體壓縮效能改進情形 8
2.1.2網路提取層 9
2.1.3視訊編碼層 10
2.1.3.1空間性預測 (Intra Prediction) 10
2.1.3.2時間性預測 (Inter Prediction) 13
2.1.3.3轉換 (Transform) 17
2.1.3.4量化 (Quantization) 18
2.1.3.5去區塊濾波器 (Deblocking Filter) 19
2-1-3-6熵編碼 (Entropy Coding) 20
2.2 H.264可調式視訊編碼器 21
2.2.1 時間可調性(Temporal Scalability) 24
2.2.2 空間可調性(Spatial Scalability) 27
2.2.2.1層際間空間預測(Inter-layer Intra prediction) 29
2.2.2.2層際間殘餘資訊預測(Inter-layer Residual prediction) 30
2.2.2.3層際間運動向量預測(Inter-layer Motion prediction) 32
2.2.3 品質可調性(Quality Scalability) 33
第三章主觀視覺品質量測 35
3.1視訊使用距離對人類視覺的影響 35
3.2主觀視覺品質量測現況介紹 36
3.3影像壓縮中的主觀視覺品質量測工具介紹 39
3.3.1主觀與客觀視覺影像品質量測[17] 39
3.3.2主觀視覺品質量測評分工具介紹 42
第四章基於主觀視覺之H.264可調式視訊編碼空間層位元率分配機制 49
4.1 H.264/SVC空間層各層QP的關係 50
4.2不同解析度下之主觀視覺品質分析 60
4.3 H.264/SVC空間層編碼架構之主觀視覺品質量測分析與結果討論 62
4.4 H.264/SVC空間層編碼架構之位元率與畫面解析度之分析 66
4.5 Q-R指數趨近線 70
4.6 Q-D線性趨近線 74
4.7基於主觀視覺之H.264可調式視訊編碼空間層位元率分配機制 78
第五章實驗結果與討論 84
5.1實驗參數環境 84
5.2基於主觀視覺之H.264可調式視訊編碼空間層位元率分配的結果分析與討論 91
5.2.1低位元率時之效能分析 91
5.2.2不同空間層數時之效能分析 95
5.2.3主觀視覺品質與固定QP位元率分配之效能比較 97
第六章結論與未來展望 105
參考文獻 107

參考文獻

[1] Advanced Video Coding for Generic Audiovisual Services, ITU-T Rec. H.264 and ISO/IEC 14496-10 (MPEG-4 AVC), ITU-T and ISO/IEC JTC 1, Version 1: May 2003, Version 2: May 2004, Version 3: Mar. 2005, Version 4: Sept. 2005, Version 5 and Version 6: June 2006, Version 7: Apr. 2007, Version 8 (including SVC extension): Consented in July 2007.
[2] H. Schulzrinne, S. Casner, R. Frederick, and V. Jacobson, “RTP: A transport protocol for real-time applications,” RFC 1889, Jan. 1996.
[3] Video Coding for Low Bit Rate communication, ITU-T Rec. H.263,ITU-T, Version 1: Nov. 1995, Version 2: Jan. 1998, Version 3: Nov.2000.
[4] Coding of audio-visual 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.
[5] Generic Coding of Moving Pictures and Associated Audio Information—Part 1: Systems, ITU-T Rec. H.222.0 and ISO/IEC 13818-1(MPEG-2 Systems), ITU-T and ISO/IEC JTC 1, Nov. 1994.
[6] Narrow-Band Visual Telephone Systems and Terminal Equipment, ITU-T Rec. H.320, ITU-T, Mar. 1993.
[7] T.Wiegand, G. J. Sullivan, J. Reichel, H. Schwarz, and M.Wien, Joint Draft 11 of SVC Amendment, Joint Video Team, Doc. JVT-X201, Jul.2007.
[8]T. Wiegand, H. Schwarz, A. Joch, F. Kossentini, and G. J. Sullivan,“Rate-constrained coder control and comparison of video coding standards,”IEEE Trans. Circuits Syst. Video Technol., vol. 13, no. 7, pp.688–703, Jul. 2003.
[9]N. S. Jayant, and P. Noll, Digital Coding of Waveforms. Englewood Cliffs, NJ: Prentice-Hall, Mar. 1984.
[10] S.-J. Choi, and J. W. Woods, “Motion-compensated 3-D subband coding of video,” IEEE Trans. Image Process., vol. 8, no. 2, pp.155–167, Feb. 1999.
[11]A. Eleftheriadis, M. R. Civanlar, and O. Shapiro, “Multipoint videoconferencing with scalable video coding,” J. Zhejiang Univ. Sci. A, vol. 7, no. 5, pp. 696–705, May 2006.
[13] T. Schierl and T. Wiegand, “Mobile video transmission using SVC,” IEEE Trans. Circuits Syst. Video Technol., vol. 17, no. 9,Sep. 2007.
[14] M. Wien, R. Cazoulat, A. Graffunder, A. Hutter, and P. Amon, “Realtime system for adaptive video streaming based on SVC,” IEEE Trans.Circuits Syst. Video Technol., vol. 17, no. 9, pp. 1227–1237, Sep. 2007.
[15] S. H. Bae, T. N ,and B.-H. Juang, “Subjective Evaluation of Spatial Resolution and Quantization Noise Tradeoffs,” IEEE Trans.Image Processing, vol. 18, no.3,March 2009.
[16] J. L. Mannos and D. J. Sakrison, “The effects of a visual fidelity criterion on the encoding of images,” IEEE Trans. Inf. Theory, vol. IT-20, no. 5, pp. 525–536, Jul. 1974.
[17]Abharana Bhat, Iain Richardson,and Sampath Kannangara,” A new percetual quality metric for compressed video,” ICASSP ,vol.51, no.3, pp. 933- 936, 2009.
[18]S. Winkler, ”A perceptual distortion metric for digital color video”, in Proc. SPIE, vol.3644, May 1999, pp.175-184.
[19] J. Lubin, and D. Fibush, “Sarnoff JND vision model”, T1A1.5Working group Document, T1 Standards Committee, 1997.
[20] A.B. Watson, J. Hu, and J.F. McGowan III, “Digital video quality metric based on human vision”,Journal of Electronic imaging, vol. 10, no.1, Jan 2001, pp. 20-29.
[21] Z. Wang, and A.C. Bovik, “A universal image quality index”, IEEE Signal Processing Letters, vol. 9, no. 3, Mar. 2002, pp. 81-84
[22] Cheon S. K., Dongjun S., Tae M. B., and Yong M. R., ”Quality Metric for H.264/AVC Scalable Video Coding with Full Scalability”SPIE Human Vision and Electronic Imaging XII, Vol.6492, 64921P, Feb. 2007
[23] ITU-R BT.500 “Methodology for the Subjective Assessment of the Quality for Television Pictures”, ITU-R Std., Rev. 11, June 2002.
[24] E.P Ong, W. Lin, Lu Zhongkang, S. Yao, and M. H. Loke, "Perceptual Quality Metric for H.264 Low Bit Rate Videos," IEEE International Conference on Multimedia and Expo, vol., no.,pp.677-680, July 2006.
[24] X. Ran, and N. Farvardin, “A perceptually motivated three component image model – Part 1: Description of the model”, IEEE Trans.On Image Processing, Vol. 4(4), 1995, pp.401- 415.
[25]Laszlo Czuni, Gergely Csaszar, and Attila Licsar,”Estimating the Optimal Quantization Parameter in H.264”, IEEE Computer Society., pp330-333, Sep. 2006.
[26] M. Narroschke, “Extending the prediction error coder of H.264/AVC by a vector quantizer ,” in Visual communications and image processing Conf., Beijing, July 2005

指導教授

張寶基(Pao-Chi Chang)

審核日期

2009-7-24

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