臺灣博碩士論文加值系統

視訊編解碼器使用在各式的視訊傳播媒體上面，除了傳統的電視機現在更用在各類的監視器以及新的應用電子產品。例如，現在電視機已經改變不再是只由CRT的傳統映像管，更有PDP電視、LCD電視、背投影電視以及投影機各種新產品的電視應用。另外，在其他電子產品方面像數位相機、數位攝錄影機、DVD錄放影機以及STB等等，還有視訊科技與電腦的結合和應用產品，如影像卡、電視視訊盒都需要使用到視訊編碼器。另一方面同時視訊編碼器也可以使用在視訊的編輯和手機做通訊結合應用，由於目前手機上的應用越來越廣泛不但可以收看影片更可以及時影音對話這些都需要視訊編碼器來達成。但是在市面上的目前視訊編碼器有許多的問題，一直以來各家廠商不斷努力於解決在視訊品質上所遇到的困擾。在這篇論文中，我們提出一個快速的移動偵測小波視訊編碼器。它可用在位元傳輸率較低在記憶體有侷限之下，以及快速的移動偵測的視訊應用上。這個視訊編碼器包含三個主要的模組。一個是3-D DWT，一個是MVFAST-PA searching以及3-D SPIHT模組。3-D DWT它的功用是將一組Video frames 的資訊做轉換使其資訊的分佈更為集中。另外一個是3-D SPIHT 模組，它的功用是將前面已轉換好的Video frames 做進一步的壓縮。此外當3-D DWT模組在執行時，我們採用MVFAST-PA searching來讓挑選移動偵測的動作變得更有效率。我們所提出的視訊編碼器有下列優點：低運算複雜度，使用少量的記憶體，以及有快速移動偵測可以在有限頻寬下做出最好的視訊編碼器。為了要評估這個被提出的視訊編碼器，我們將它與Gokturk和Aaron所提出的3-D 方法視訊編碼器做比較。 我們做了完整的實驗，結果顯示我們所提出的視訊編碼器的編碼速度和畫面顯示會優於Gokturk和Aaron[1]所提出的3-D視訊編碼器

Video compression has been an active research area in the last decade. Amongst many proposed methods, motion compensated coding has taken the most attention and taken its place in many standards (Mpeg, H.26L, etc…) The main difference between motion compensated coding and image based coding schemes such as DWT is that motion compensated coding exploits temporal redundancies between consecutive frames, i.e., between two frames. In this paper, we propose a new architecture of Video encoding method for low bandwidth application. The new architecture video codec consists of three main modules, the 3-D DWT transform module that performs an energy compaction of a group of video frames and the modified 3-D listless zero-tree coding module that further codes the transformed video frames. When executing the modified 3-D listless zero-tree coding module, the 3-D asymmetric parent-child relations are used for sorting the 3-D wavelet coefficients more effectively. Advantageous features of the new architecture video codec include low computational complexity, memory-efficient, and fasting motion vector search. To evaluate the proposed video codec, we have compared it with the 3-D methods to video codec proposed by Gokturk and Aaron. Extensive simulations have been conducted. The simulation results show that a fasting search is obtained with this video codec compared to the 3-D methods to video codec.

中文摘要 II
ABSTRACT III
第一章 緒論 1
第1-1節 研究背景 1
第1-2節 研究動機 1
第二章 相關背景 4
第2-1節 視訊系統 4
第2-2節 影像表示法 7
第2-3節 濾波器比較研究 10
第2-4節 影像傳輸 14
第2-5節 影像處理 15
第2-6節 影像轉換 17
第2-7節 影像壓縮 27
第三章 新架構視訊編碼方法 28
第3-1節 3D移動補償編碼 28
第3-2節 新架構視訊編碼方法 33
第 四 章 實驗與比較 45
第4-1節移動偵測比較 45
第4-2節PSNR比較 46
第4-3節 編碼影像比較 47
第 五 章 結論與未來研究 49
第5-1節 結論 49
第5-2節 未來研究 49

參考文獻 50

[1] S. B. Gokturk and A. M. Aaron, "Applying 3D Methods to Video for Compression", Digital Video Processing (EE392J) Projects Winter Quarter, 2002
[2] A. Said and W. A. Pearlman, “A New Fast and Efficient Image Codec Based on Set Partitioning in Hierarchical Trees,” IEEE Trans. on Circuits and Systems for Video Technology, Vol. 6, No. 3, pp. 243-250, Jun. 1996
[3] B. J. Kim and W. A. Pearlman, “An embedded wavelet video coder using three-dimensional set partitioning in hierarchical trees (SPIHT),” Proc. IEEE Data Compression Conf., pp. 251-260, Mar. 1997
[4] B. J. Kim, Z. Xiong, and W. A. Pearlman, “Low Bit-Rate Scalable Video Coding with 3-D Set Partitioning in Hierarchical Trees (3-D SPIHT),” in IEEE Trans. on Circuits and Systems for Video Technology., vol. 10, No. 8, pp. 1374-1387, Dec. 2000
[5] P. L. Dragotti, G. Poggi, and A. R. P. Ragozini, “Compression of multispectral images by three-dimensional SPIHT algorithm”, in IEEE Trans. On Geoscience and remote sensing, vol. 38, No. 1, pp. 416-428, Jan. 2000
[6] CHEN Guo-bin , “A fast motion estimation algorithm for mobile communications” Journal of Zhejiang University SCIENCE ISSN 1862-1775, Dec. 2005
[7] Forman, M.C., Aggoun, A., McCormick, M., “A novel coding scheme for full parallax 3D-TV pictures, ” Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 4, pp. 2945–2947, Apr. 1997
[8] Abousleman, G.P., Marcellin, M.W., and Hunt, B.R., “Compression of hyperspectral imagery using the 3-D DCT and hybrid DPCM/DCT, “IEEE Transactions on Geoscience and Remote Sensing, vol. 33, Issue 1, pp. 26–34, Jan. 1995
[9] Bauer, M and Sayood, K., “Video coding using 3 dimensional DCT and dynamic code selection,” .Proc. IEEE Data Compression Conference, pp. 451, Mar. 1995
[10] Chan, R.K.W.and Lee, M.C, “3D-DCT quantization as a compression technique for video sequences,”Proc. International Conference on Virtual Systems and MultiMedia, 1997. VSMM ''97. Proceedings, pp. 188–196, Sept. 1997, Geneva, Switzerland.
[11] Jingmin Song, Zhang Xiong, Xudong Liu and Yun Liu, “PVH-3DDCT: an algorithm for layered videocoding and transmission,” Proc. The Fourth High Performance Computing in the Asia-Pacific Region, vol. 2, pp. 700–703, May 2000, Beijing, China.
[12] D.G.Sampson, E.A.B. de Silva, and M. Ghanbari, “Low bit-rate video coding using Waveletquantization”, Proc. Inst. Elect. Eng., vol. 142, pp.141-148, 1995
[13] Gi Hun Lee; Joon Ho Song; Rae-Hong Park, “Three-dimensional DCT/WT compression using motionvector segmentation for low bit-rate video coding,” Proceedings of International Conference on Image Processing, vol.3, pp. 456 -459, 1997
[14]Vass, J.; Bing-Bing Chai; Xinhua Zhuang, “3DSLCCA-a highly scalable very low bit rate software-only wavelet video codec “,Proc. IEEE Second Workshop on Multimedia Signal Processing, pp. 474–479, Dec. 1998, Redondo Beach, CA, USA.
[15] Gang Lin and Zemin Liu, “3D wavelet video codec and its rate control in ATM network,” Proc. IEEE International Symposium on Circuits and Systems, vol. 4, pp. 447–450, Jun. 1999, Orlando, FL.
[16] Bernabe, G.; Gonzalez, J.; Garcia, J.M.; Duato, J., “A new lossy 3-D wavelet transform for highquality compression of medical video”, IEEE EMBS International Conference on Information Technology Applications in Biomedicine, pp. 226–231, 2000
[17]. Lazar, D.; Averbuch, A., “Wavelet-based video coder via bit allocation,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 7, pp. 815–832, Jul. 2001
[18] Seigneurbieux, P. and Zixiang Xiong, “3-D wavelet video coding with rate-distortion optimization,” Proc. International Conference on Information Technology: Coding and Computing, pp. 322–326, April 2001, Las Vegas, NV, USA
[19] J.M. Shapiro, “Embedded image coding using zerotrees of wavelet coefficients,” IEEE Transactions on Signal Processing, vol. 41, no. 12, pp. 3445-3462, December 1993.
[20] Gokturk SB, Tomasi C, Girod B, Beaulieu CF, “Medical Image Compression Based on Region of Interest, with Application to Colon Ct Images,” in 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Istanbul, Turkey, 2001.
[21] J.S. Taur, and C.W. Tao, “Medical Image Compression using Principal Component Anlyasis,” International Conference on Image Processing, vol.2, pp. 903 -906, 1996
[22] M. Yoshioka, and S. Omatu, “Image Compression by nonlinear principal component analysis,” IEEE Conference on Emerging Technologies and Factory Automation, EFTA ''96, vol. 2, pp. 704-706, 1996