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結論與未來展望

在文檔中 利用階層分解之視訊壓縮 (頁 78-82)

本篇論文使用的編碼方式是把影像分成前景和背景來討論,希望依照壓縮的 需求以不同的編碼方式來達到編碼效率的改善。在此編碼效能之改善為1.前景的 部分PSNR 品質的提升、2.背景的部分減少資料壓縮量與 3.整體壓縮時間減少,

針對這些部分,利用到區塊大小和Rate-Distortion 的參數值設定,的確可以有效 改善前景的畫面品質和背景的資料量。

由於整個H.264 標準的架構非常龐大,可以再分析的部分也很多,如量化參 數、參考畫面數、Entropy 編碼等,都可能繼續應用在前景和背景的壓縮。在本 篇論文,我們都以符合標準的解碼程序來做研究,當然,如果能在標準規定的語 法和語意外來進行編碼,前景和背景分析的結果,應該會有更大的空間發展。

在本論文中亦提出了一個自動切割的方法,從實驗顯示,本方法可以切割出 與攝影機運動不同的物體,比較可能切割錯誤的地方在於畫面中一大片的平滑區 域,造成的原因如 5.3 小節所敘述,乃是因為區塊比對誤差所造成,而使用光流 估測的方法亦會有同樣的缺點,因此區域運動估測與對應點的改善是一個重要的 課題。另外,本論文所提出的方法可以切割出前景與背景兩個區域,考慮其他的 應用下,可以再詳細對不同運動的物體做切割,例如將Mobile 影片中的月曆、

球與火車各自切割,此為後續可研究的方向之一。由於大多數的壓縮標準均以區 塊為壓縮單位,所以以區塊為基礎的切割方法中,可以適用於多數的壓縮標準,

若考慮以MPEG4 之 VOP [8]為壓縮單位,可以考慮使用本論文的方法在切割好 的物體之中,再針對每個物體的輪廓做細部切割。本論文亦可當成其他視訊切割 方法的基礎,例如,只切割一張影像並找出獨立運動的物體當成初始切割,之後 可能使用物體追蹤之方式,繼續對不同的畫面做切割。

參考文獻

[1] ITU-T Rec. H.264 / ISO/IEC 11496-10, “Advanced Video Coding,” Final Committee Draft, Document JVT- E022, September 2002.

[2] ITU-T Rec. H.264 / ISO/IEC 11496-10, “Advanced Video Coding,” Final Committee Draft, Document JVT-F100, December 2002.

[3] Iain E G Richardson, “H.264 and MPEG-4 Video Compression,” John Wiley &

Sons, 2003.

[4] ITU-T Rec. H.264 / ISO/IEC 11496-10, “Advanced Video Coding,” Final Committee Draft, Document JVT-G050, March 2003

[5] 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.

[6] T. Wiegand, H. Schwarz, A. Joch, F. Kossentini and G. J. Sullivan,

“Rate-Constrained Coder Control and Comparison of Video Coding Standards,”

IEEE Transactions on Circuits and Systems for Video Technology, vol. 13, no.7,

pp. 688 – 703, 2003.

[7] M. Flierl and B. Girod, “Generalized B Pictures and The Draft H.264/AVC video-compression standard,” IEEE Transactions on Circuits and Systems for

Video Technology, vol. 13 , no. 7 , pp.587 – 597, 2003.

[8] ISO/IEC IS 11172-2, MPEG-1 Video.

[9] ISO/IEC IS 13818-2, MPEG-2 Video.

[10] ISO/IEC IS 14996-2, MPEG-4 Video.

[11] JVT Reference Software, ftp://ftp.imtc-files.org/jvt-experts/reference_software/ . [12] R. C. Gonzalez and R. E. Woods, “Digital Image Processing,” Prentice Hall, 2

edition, 2002

[13] M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: Active Contour Models,” Int.

Journal of Computer Vision, vol. 1, pp. 321~331, 1988.

[14] L. Vincent and P. Soille, “Watersheds in digital spaces: an efficient algorithm base on immersion simulations,” IEEE Transactions on Pattern Analysis and

Machine Intelligence, vol. 13, pp. 583~598, 1991.

[15] J. Shi and J. Malik, “Normalized Cuts and Image Segmentation,” IEEE

Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 8, Aug.

2000.

[16] R. Castango, T. Ebrahimi and M. Kunt, “Video Segmentation Based on Multiple Features for Interactive Multimedia Application,” IEEE Transactions on Circuits

and Systems for Video Technology, vol. 8, no. 5, Sept. 1998.

[17] S. Y. Chien, S. Y. Ma, and L. G. Chen, “Efficient Moving Object Segmentation Algorithm Using Background Registration Technique,” IEEE Transactions on

Circuits and Systems for Video Technology, vol. 12, no. 7, July 2002

[x] R. Mech and M. Wollborn, “A noise robust method for segmentation of moving objects in video sequences,” Proc IEEE Int. Conf. Acoustics, Speech, Signal

Processing, ICASSP’97, Munich, Germany, Apr. 1997, vol. 4, pp. 2657–2660.

[18] G. Adiv, “Determining three-dimensional motion and structure from optical flow generated by several moving objects,” IEEE Transactions on Pattern Analysis

and Machine Intelligence, vol. PAMI-7, pp. 384–401, July 1985.

[19] B. J. Frey, N. Jojic, and A. Kannan, “Learning Appearance and Transparency Manifolds of Occluded Objects in Layers,” Proc. Computer Vision and Patten

Recognition, vol. 1, pp. 45–52, Madison, WI, 2003.

[20] J. Shi and J. Malik, “Motion Segmentation and Tracking Using Normalized Cuts,” IEEE Int. Conf. Computer Vision, pp. 1154-1160, 1998.

[21] T. Meier and K. N. Ngan, “Automatic Segmentation of Moving Objects for Video Object Plane Generation,” IEEE Transactions on Circuits and Systems for

Video Technology, vol. 8, no. 5, Sept. 1998.

[22] J. G. Choi, S. W. Lee, and S. D. Kim, “Spatio-Temporal Video Segmentation Using a Joint Similarity Measure,” IEEE Transactions on Circuits and Systems

for Video Technology, vol. 7, no. 2, April 1997.

[23] R. V. Babu, K. R. Ramakrishnan, and S. H. Srinivasan “Video Object Segmentation: A Compressed Domain Approach” IEEE Transactions on Circuits

and Systems for Video Technology, vol. 14, no 4, pp. 462-474, 2004.

[24] Z. G. Li, F. Pan, K. P. Lim, G. N. Feng, X. Lin, S. Rahardia, D.J. Wu, “Adaptive frame layer rate control for H.264,”IEEE Int. Conf. Multimedia and Expo, vol. 1, pp.581–584, 6–9 July 2003.

[25] Y. Lu, W. Gao, and F. Wu, “Efficient Background Video Coding With Static Sprite Generation and Arbitrary-Shape Spatial Prediction Techniques,” IEEE

Transactions on Circuits and Systems for Video Technology, vol. 13, no 5, pp.

394-405, 2003.

[26] F. Pan, X. Lin, S. Rahardja, K. P. Lim, Z. G. Li, D. Wu, and S. Wu “Fast Mode Decision Algorithm for Intraprediction in H.264/AVC Video Coding” IEEE

Transactions on Circuits and Systems for Video Technology, vol. 15, no 7, pp.

813-822, 2005.

[27] Z. K. Lin, H. H. Lin, Y. H. Chen, and J.H. Chuang, “On The Performance Improvement Of H.264 Through Foreground and Background Analysis” IEEE

Int. Conf. Multimedia and Expo, 6–8 July 2005.

[28] B. K. P. Horn and B. G. Schunck, “Determining Optical Flow,” Artif. Int., vol. 17, pp. 185–203, 1981.

[29] Y. P. Tan, S. R. Kulkarni, and P. J. Ramadge, “A New Method for Camera Motion Parameter Estimation,” Proc. IEEE Int. Conf. Image Processing, vol. 1, pp. 406–409, Oct. 1995.

[30] Y. P. Tan, D. D. Saur, S. R. Kulkarni, and P. J. Ramadge, “Rapid Estimation of Camera Motion from Compressed Video with Application to Video Annotation,”

IEEE Transactions on Circuits and Systems for Video Technology, vol. 10, no. 1, Feb. 2000.

在文檔中 利用階層分解之視訊壓縮 (頁 78-82)