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研究生:葉姿霈
研究生(外文):Chih-PeiYeh
論文名稱:應用於深度資訊立體視訊之以物件為基礎的畫面內插演算法
論文名稱(外文):An Object-based Frame Interpolation Algorithm for Depth-based 3-D videos
指導教授:戴顯權戴顯權引用關係
指導教授(外文):Shen-Chuan Tai
學位類別:碩士
校院名稱:國立成功大學
系所名稱:電腦與通信工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:英文
論文頁數:57
中文關鍵詞:動作向量估計動作補償畫面內插畫面頻率提升
外文關鍵詞:motion estimationmotion-compensated frame interpolationframe rate up-conversion
相關次數:
  • 被引用被引用:1
  • 點閱點閱:129
  • 評分評分:
  • 下載下載:17
  • 收藏至我的研究室書目清單書目收藏:1
畫面頻率提升演算法是一種提高低畫面頻率影片的視覺品質的技術。在大多數的畫面頻率提升演算法中,使用以區塊為單位的動作向量預估方式,而容易產生方塊效應,影響畫面的視覺品質。在這篇論文中,我們提出了一個基於立體影片的深度資訊,改良擬真動作預估來提升畫面頻率。在我們提出的動作預估演算法中,由於深度資訊區分為不同資訊的動作向量會被分開更新,亦即在不同物件的像素會被給予不同的動作向量。因此我們可以得到以物件為單位且更為準確的動作向量,使得畫面頻率提升的品質更佳。而對於重複覆蓋的區域,也能以深度資訊來從候選動作向量中選取最適當的動作向量。實驗結果顯示,在主觀和客觀上,即便是在較為複雜和有較快動作的場景,我們的演算法都可以有效改良畫面頻率提升後的影片品質。
Frame rate up-conversion (FRUC) is a visual quality enhancement technology for the low frame rate video. Most FRUC algorithms use the block-based motion estimation and it may cause blocking artifacts which will affect the quality of the video. In this thesis, we present an improved multi-pass true motion estimation algorithm based on 3D videos for FRUC. In the proposed algorithm, the motion vectors of different objects which are parted with the depth information of 3D videos will be refined independently. Pixels in different objects will be referred to diverse motion vectors. Therefore, more accurate object–based motion vectors can be obtained which causes the performance of FRUC. For overlapped regions, the motion vector will be chosen in candidates by depth information. Experimental results show that the proposed algorithm effectively enhances the overall quality of the frame rate up-converted video sequence, both subjectively and objectively, even with complex scenes and fast motion.
Contents....................................... iv
List of Tables ....................... vi
List of Figures ....................................... vii
Chapter 1 Introduction .................................. 1
Chapter 2 Background and Related Work.................... 4
2.1 H.264/AVC Standard .......................... 4
2.1.1 Video Encoding ............................. 4
2.1.2 Intra-frame Prediction ........................... 5
2.1.3 Inter-frame Prediction ........................... 5
2.1.4 H.264/AVC Video Data Hierarchy ................. 6
2.2 Multi-View Video Coding .............................. 7
2.2.1 Stereo Video Coding ............................... 7
2.2.2 Depth-Map .................................... 8
2.3 Motion Compensated Frame Interpolation .......... 9
2.4 Dual Motion Estimation .......................... 11
2.5 Multistage Motion Vector Processing Method ...... 15
2.5.1 Motion Vector Reliability Classification ........ 15
2.5.2 Macroblock Merging Based on Motion Vector Reliability ........... 16
2.5.3 Motion Vector Selection .......................... 16
2.5.4 Motion Vector Reclassification ................ 17
2.5.5 Motion Vector Refinement ........................ 18
2.6 True Motion Estimation ....................... 19
2.6.1 Predictive Motion Vector ........................ 20
2.6.2 Update Vector Set .............................. 22
2.6.3 Distortion Criterion ............................ 22
Chapter 3 The Proposed Object-based Frame Interpolation Algorithm ............................................ 23
3.1 Region Classification ........................ 25
3.2 Improved Multi-pass True Motion Estimation ......... 27
3.3 Overlapped Regions Process ................. 31
3.4 Frame Interpolation ..................... 32
3.5 Uncovered Regions Process ................. 32
Chapter 4 Experimental Results ........................ 34
4.1 Test Environment ....................... 34
4.2 Experimental Results ......................... 35
Chapter 5 Conclusions and Future Works ................. 53
5.1 Conclusions ......................................... 53
5.2 Future Works ....................................... 54
Reference ............................................. 55
Biography ......................... 57
[1] A. M. Tekapl, Digital Video Processing. Englewood Cliffs, NJ: Prentice Hall, 1995.
[2] A. N. Netravali and J. D. Robbins, “Motion-adaptive interpolation of television frames, in Proc. Picture Coding Symp., Jun. 1981, p. 115.
[3] B. D. Choi, J. W. Han, C. S. Kim, and S. J. Ko, “Frame rate up-conversion using perspective tranform, IEEE Trans. Consumer Electron. vol.52, no.3, 2006, pp. 975-982.
[4] K. Sugiyama, T. Aoki, and S. Hangi, “Motion compensated frame rate conversion using normalized motion estimation, in Proc. IEEE Workshop Signal Process. Syst., 2005, pp. 663-668.
[5] S. J. Kang, S. Yoo, and Y. H. Kim, “Dual motion estimation for frame rate up-conversion, IEEE Trans. Circuits and Syst. Video Technol., 2010, pp. 1909-1914
[6] A. M. Huang and T.Q. Nguyen, “A multistage motion vector processing method for motion-compensated frame interpolation, IEEE Trans. Image Process., 2008, pp. 694-708.
[7] C. Wang, L Zhang, Y He, and Y. P. Tan, “Frame rate up-conversion using trilateral filtering, IEEE Trans. Circuits and Syst. Video Technol., 2010, pp.
[8] G. Dane and T. Q. Nguyen, “Optimal temporal interpolation filter for motion-compensated frame rate up conversion, IEEE Trans. Image Process., vol. 15, no. 4, pp. 978–991, Apr. 2006.
[9] L. Alparone, M. Barni, F. Bartolini, and V. Cappellini, “Adaptively weighted vector-median filters for motion-fields smoothing, in Proc. ICASSP, May 1996, vol. 4,
56
pp. 2267–2270.
[10] G. Dane and T. Q. Nguyen, “Motion vector processing for frame rate up conversion, in Proc. ICASSP, May 2004, vol. 3, pp. 309–312.
[11] B. Girod, “Efficiency analysis of multihypo thesis motion-compensated prediction for video coding, IEEE Trans. Image Process., vol. 9, no. 2, pp. 173–183, Feb. 2000.
[12] J. Zhai, K. Yu, J. Li, and S. Li, “A low complexity motion compensated frame interpolation method, in Proc. ISCAS, May 2005, vol. 5, pp. 4927–4930.
[13] Y. T. Yang, Y. S. Tung, and J. L. Wu, Quality enhancement of frame rate up-converted video by adaptive frame skip and reliable motion extration, IEEE Trans. Circuits and Syst. Video Technol., 2007, pp. 1700-1713.
[14] S. C. Tai, Y. R. Chen, Z. B. Huang, and C. C. Wang, “ A multi-pass true motion estimation scheme with motion vector propagation for frame rate up-conversion applications, IEEE/OSA Journal of Display Technology, 2008, pp.188-197.
[15] C. S. Hong, C. C. Wang, S. C. Tai, Y. C. Luo, “Object-based error concealment in 3D video, International Conference on Genetic and Evolutionary Computing (ICGEC), 2011, pp. 5-8.
[16] Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: Form error visibility to structural similarity, IEEE Trans. Image Process., 2004, pp. 600-612.
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