博碩士論文 985202109 詳細資訊




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姓名 邱家揚(Chia-yang Chiou)  查詢紙本館藏   畢業系所 資訊工程學系
論文名稱 基於結構相似度之H.264/AVC視訊畫面品質恆定控制
(SSIM-Based Constant Frame Quality Control for H.264/AVC)
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摘要(中) 數位視訊需經有效的資料壓縮程序以利其傳輸與儲存。然而,壓縮後的視訊畫質並不易受到控制,連續畫面品質的劇烈變動,可能造成若干視覺上的失真。若相關應用需要將每張畫面內容適當地保存,只考慮位元率控制的編碼機制也許並不是非常適合。本研究提出視訊畫質恆定控制技術,減少視訊畫面間的品質差異,提升視訊觀賞的流暢度與舒適感,有利於重要資料的保存。此外,如果我們能夠在編碼前即合理預測視訊畫質與編碼參數間的關係,對於位元率控制編碼也將有所助益。
  以往的視訊畫質估測經常採用均方誤差的方式,但均方誤差與人眼視覺之間缺乏良好的相關性。因此研究人員提出了各種畫質估測方式,而結構相似性指標(SSIM)是其中之一。由於結構相似性指標有效地模擬人眼視覺系統中擷取影像結構訊息的功能,所以我們採用結構相似性指標做為畫質量測依據,並藉此提出失真-量化參數預測模型、模型參數的預測方法以及實際編碼中的動態處理程序等,以達成畫面品質恆定控制之目的。與H.264/AVC參考軟體JM相較,我們所提出的方法不僅大幅降低了畫面品質的變化,在同樣的整體視訊品質下,也擁有較低的位元率。
摘要(英) The digital videos require effective compression to facilitate their transmission and storage. However, it is not easy to control the quality of compressed videos. If the related applications need to preserve the content of every frame in the video, the traditional rate control mechanism may not be suitable. In this research, we propose a constant frame quality control technique, which can reduce the quality variations between successive frames to avoid serious perceptual distortion. The proposed scheme may thus be helpful in the applications of video archiving or surveillance videos. In addition, by constructing the relationship between the quality and quantization parameter, the proposed method may also benefit the traditional rate control coding.
Objective distortion metrics such as mean squared error or peak signal to noise ratio are poorly correlated with the human perceptual quality. Recently, various image/video quality metrics based on the HVS have been proposed and the structural similarity (SSIM) index has been shown to be effective. Therefore, we adopt SSIM as the quality metric for our constant frame quality control. Compared with the reference software of H.264/AVC, JM, our approach can reduce SSIM variation significantly. Furthermore, at the same SSIM index, the proposed scheme achieves lower overall bit-rate.
關鍵字(中) ★ 失真-量化參數預測模型
★ 結構相似度
★ 畫面品質恆定控制
★ 視訊編碼
關鍵字(英) ★ SSIM
★ H.264/AVC
★ constant frame quality
★ D-Q model
論文目次 第一章 緒論 ..1
1-1 研究目的與動機 ..1
1-2 貢獻 ..4
1-3 論文架構 ..5
第二章 相關研究與技術 ..6
2-1 相關研究 ..6
2-2 SSIM的概念與計算方式 ..7
2-3 H.264/AVC之預測編碼模式 ..10
2-2-1 Intra模式 ..10
2-2-2 Inter模式 ..11
第三章 研究方法 ..12
3-1 概述 ..12
3-2 D-Q model ..15
3-2-1 基礎單位 ..15
3-2-2 最佳QP值 ..19
3-2-3 失真-量化參數模型建立 ..19
3-3 參數預測 ..21
3-4 預測方法 ..25
3-4-1 高斯模糊化 ..26
3-4-2 奇異值分解 ..27
3-4-3 預測值結合與實驗數據 ..29
3-5 多層級預測模型與參數值 ..32
3-6 動態處理 ..33
3-6-1 關鍵畫面機制與SSIM控制程序實施的編碼模式基礎 ..33
3-6-2 D-Q model校正 ..35
3-6-3 動態處理程序 ..36
3-7 流程圖 ..37
第四章 實驗結果 ..39
4-1 實驗環境與設定 ..39
4-2 SSIM恆定控制 ..40
4-3 P frame實驗 ..45
4-4 實驗數據比較 ..47
4-5 複雜度比較 ..51
4-6 主觀審視畫面品質 ..52
第五章 結論 ..57
第六章 參考文獻 ..58
參考文獻 [1] Draft ITU-T Recommendation and Final Draft International Standard of Joint Video Specification. ITU-T Rec. H.264 and ISO/IEC 14496-10 AVC, Document JVT-G050.doc, Pattaya, Thailand, 2003.
[2] T. Wiegand, H. Schwarz, A. Joch, F. Kossentini, and G. J. Sullivan , "Rate-constrained coder control and comparison of video coding standards"
[3] Z. Wang and A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, "Image quality assessment: From error visibility to structural similarity," IEEE Trans. Image Process, vol. 13, no. 4, pp. 600-612, Apr. 2004.
[4] M. H. Pinson and S. Wolf, "A new standardized method for objectively measuring video quality," IEEE Trans. Broadcasting, vol. 50, no. 3, pp. 312-322, Sep.2004.
[5] T. J. Liu, K. H. Liu and H. H. Liu, "Temporal information assisted video quality metric for multimedia," IEEE International Conference on Multimedia and Expo (ICME), pp.697-701, Jul. 2010.
[6] A. K. Moorthy and A. C. Bovik, "Efficient video quality assessment along temporal trajectories," IEEE Trans. Circuits and systems for video technology, vol. 20, no. 11, Nov. 2010.
[7] Y. H. Huang, T. S. Ou, P. Y. Su and Homer H. Chen, "Perceptual rate-distortion optimization using structural similarity index as quality metric," IEEE Trans. Circuits and systems for video technology, vol. 20, no 11, Nov.2010.
[8] T. S. Ou, Y. H. Huang and Homer H. Chen, "SSIM-based perceptual rate control for video coding," IEEE Trans. Circuits and systems for video technology, vol. 21, no. 5, Mar. 2011.
[9] JVT reference software. [online]. Available:http://iphome.hhi.de/suehring/tml/
[10] VQEG FRTV Phase I databese. [online]. Available:ftp://ftp.crc.ca/crc/vqeg/TestSequences/
[11] LIVE Video Quality Database. [online]. Available:http://live.ece.utexas.edu/research/quality/live_video.html
[12] Z. He, W. Zeng and C. W. Chen, "Low-Pass Filtering of Rate Distortion Functions for Quality Smoothing in Real-Time Video Communication," IEEE Trans. Circuits and systems for video technology, vol. 15, no 8, Aug.2005.
[13] N. Cheniavsky, "MultiStage:a MINMAX bit allocation algorithm for video coders," IEEE Trans. Circuits and systems for video technology, vol. 17, no. 1, Jan.2007.
[14] B. Han and B. Zhou, "VBR rate control for perceptually consistent video quality," IEEE Trans. Consumer Electronics, vol. 54, no. 4, Nov.2008.
[15] K. L. Huang and H. M. Hang, "Consistent Picture Quality Control Strategy for Dependent Video Coding," IEEE Trans. Circuits and systems for video technology, vol. 18, no. 5, May.2009.
[16] Z. G. Li, F. pan, K. P. Lim, G. N. Feng, X. Lin, and S. Rahardaj, Adaptive basic unit layer rate control for JVT, Joint Video Team of ISO/IEC JTC1/SC29/WG11 and ITU-T SG16/Q.6 Doc. JVT-G012, Pattaya, Thailand, Mar. 2003.
[17] S. Ma, W. Gao, and Y. Lu, “Rate-distortion analysis for H.264/AVC video coding and its application to rate control,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 15, no. 12, pp. 1533–1544, Dec.2005.
[18] N. Kamaci, Y. Altunbasak, and R. M. Mersereau, “Frame bit allocation for the H.264/AVC video coder via cauchy density-based rate and distortion models,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 15, no. 8, pp. 994–1006, August 2005.
[19] C. Y. Wu and P. C. Su, “A content-adaptive distortion-quantization model for intra coding in H.264/AVC,” The 20th IEEE International Conference on Computer Communication Networks (ICCCN 2011), Maui, Hawaii, July 31-Aug, 4, 2011.
[20] J. L. Devore, and N. R. Farnum, Applied Statistics for Engineers and Scientists. New York: Duxbury, 1999.
[21] P. C. Su, H. M. Chang and M. L. Li, "A content authentication scheme for images/videos based on feature extraction and digital watermarking," Computer Vision, Graphics and Image Processing Conference (CVGIP), pp. 12-19, Aug. 19-21, 2007.
[22] G. Bradski, A. Kaehler, “Learning OpenCV: computer vision with the
OpenCV library”, O'Reilly Media, Inc., 2008.
指導教授 蘇柏齊(Po-chyi Su) 審核日期 2011-8-22
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