Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/8062
標題: 基於低複雜度內插之新型移動適應性視訊解交錯演算法設計與實作
Novel LCI-based Motion Adaptive De-interlace Technology for Video Post-processing
作者: 何恭政
He, Gong-Zheng
關鍵字: De-interlace;解交錯
出版社: 電機工程學系所
引用: 英文參考文獻: [1] Shyh-Feng, Yu-Ling Chang, and Liang-Gee Chen, “Motion Adaptive Interpolation with Horizontal Motion Detection for Deinterlacing”, IEEE Transactions on Consumer Electronics.Volume 49, Issue 4, pp. 1256 – 1265, Nov. 2003. [2] Yang Yuhong, Chen Yingqi, and Zhang Wenjun, “Motion Adaptive Deinterlacing Combining with Texture Detection and Its FPGA Implementation”, Proceeding of 2005 IEEE International Workshop on VLSI Design and Video Technology, pp. 316-319, May . 2005. [3] Yung Yuhong, Chen Yingqi, Zhung Wenjun ,”Motion adaptive deinterlacing combining with texture detection and its FPGA implementation” , Proceedings of 2005 IEEE International Workshop on VLSI Design and Video Technology, pp. 316 – 319, 28-30, May. 2005. [4] Yanfei Shen, Dongming Zhang, Yongdong Zhang and Jintao Li, Member IEEE, “Motion Adaptive Deinterlacing of Video Data with Texture Detection“ , Proceedings of the 2004 International Symposium on Circuits and Systems, Volume 2, pp. II - 213-16 , 23-26, May. 2004. [5] Ching-Ting Hsu, Mei-Juan Chen and Chin-Hui Huang Department of Electrical Engineering National Dong Hwa University, Taiwan ”High Performance Spatial -Temporal De-interlacing Technique Using Interfield Information” IEEE Trans. on Consumer Electronics, Volume 2, Page, Nov. 2004. [6] Ho Young Lee, Jin Woo Park, Sang Um Choi, Tae Min Bae, and Yeong Ho Ha, “Adaptive Scan Rate Up-Conversion System Based on Human Visual Characteristics”, IEEE Trans Consumer Elec., Volume 46, Issue 4, pp. 999-1006, Nov. 2000. [7] Hossein Mahvash Mohammadi, Pierre Langlois, and Yvon Savaria “A Five-Field Motion Compensated Deinterlacing Method Based on Vertical Motion“, IEEE Transactions on Consumer Electronics, Volume 53, Issue3, pp. 1117 – 1124 , Aug. 2007. [8] Pei-YinCHEN ,Memberand Yao-HsienLAI , Nonmember ”A Low-Complexity Interpolation Method for Deinterlacing”, Transactions on Information and Systems archive Volume E90-D,Issue 2 table of contents, pp. 606-608, February. 2007. [9] S. C. Tai, C. S. Yu, and F. J. Chang Department of Electronic Engineering, National Cheng Kung Universiq, Taiwan, R.0.C “A Motion and Edge Adaptive Deinterlacing Algorithm” IEEE International Conference on Multimedia and Expo.Volume 1, pp.659 - 662 , 30-30, June. 2004. [10] P. Brox, I. Baturone, S. Sanchez-Solano” Interlaced to progressive scan conversion Using fuzzy edge-based line average algorithm” , IEEE International Workshop on Intelligent Signal Processing,1-3 Sept. pp.10 – 15, 2005. [11] Kenju Sugiyama and Hiroya Nakamura, “A Method of Deinterlacing with Motion Compensated Interpolation”, IEEE Trans Consumer Elec , Volume 45, no.3, pp.611-616, August. 1999. [12] Kefei Ouyang , Guobin Shen , Shipeng Li , Ming Gu “Advanced Motion Search and Adaptation Techniques for Deinterlacing” IEEE International Conference on Multimedia and Expo,6-6 , pp:374 – 377, July. 2005. [13] KenjiSugiyama Yoshiyuki Yamada Naoya Sagara ”Improvement of Motion Compensated Inter-Field Interpolation Method for De-Interlacing” IEEE Region 10 Conference, pp.1 – 4, Nov. 2006. [14] Yu-LinChang,Ping-HaoWu,Shyh-FengLin,andLiang-GeeChen”Four field local motion compensated de-interlacing” , IEEE International Conference on Acoustics, Speech, and Signal Processing Volume 5 , pp: V - 253-6, 17-21 May. 2004. [15] Gwo Giun Lee, Hsin-Te Li,Ming-Jiun Wang, and He-Yuan Lin “Motion Adaptive Deinterlacing via Edge Pattern Recognition” IEEE International Symposium on Circuits and Systems, pp.2662 – 2665, 27-30 May. 2007. [16] Hoon Yo and Jechang Jeong “Direction oriented interpolation and its application to de-interlacing”,IEEE Transactions on Consumer Electronics, Volume.48, No. 4, Nov. 2002. [17] Min Kyu Park, Moon Gi Kang, Kichul Nam, and Sang Gun Oh “New edge dependent deinterlacing algorithm based on horizontal edge pattern” IEEE Transactions on Consumer Electronics, Volume. 49, No. 4, Nov. 2003. 中文參考文獻: [18] 北瀚科技股份有限公司SMIMS Engine Software Development Kits User Guide VeriLite USB V2 Version 2007.8. [19]夏湘玲 ”Motion and Pattern De-interlace Algorithm” 中原大學論文 2005.7. 參考網頁: [20] http://doom9.cdpa.cc/index.html?/video-basics.htm [21] http://www.hoyo.idv.tw/data/video.htm [22] http://video.ee.ntu.edu.tw/~video/homework/hw1/PSNR.pdf
摘要: 
近年來人們對於顯示器的畫質要求愈來愈高,隨著平面顯示器的日漸普及,解交錯處理也變成了一項非常重要的技術。目前在台灣所看見的電視節目,一般來說是使用NTSC系統的交錯式畫面,為了要讓交錯式畫面能顯示在循序式的掃描平面顯示器,且得到更好的畫質,就得依賴解交錯演算法的處理。
本論文內容為提出一個基於低複雜度內插之新型移動適應性視訊解交錯演算法設計與實作。本演算法採用了新型的移動適應性演算法,除了在四張場的動態偵測的部份,改善了原來因為物體反彈而判斷錯誤的四,另外將移動適應性演算法中,畫面由區分為動、靜二個部份,改成分為動、靜、不確定動靜三個部份,將畫面分的更明顯,接著再以三種針對其部份的演算法處理。除了靜態是採用場間平均內插法外,動態與不確定動靜態部份所使用的演算法,都是基於低複雜度內插法所發展出來的演算法,動態部份我們是希望能將偵測的範圍拉大,故發展了大範圍偵測型低複雜內插法,而不確定動靜態部份,我們希望能參考到時間性演算法與空間性演算法,故發展出了三維中間值低複雜內插法。
本論文提出的演算法,是在不使用移動補償處理與遮罩處理的情況下,盡量去節省運算量以達到高品質的解交錯影像結果。最後FPGA的功能驗證,我們使用了北瀚科技股份有限公司所出產的系統平台做功能驗證處理,經由Xilinx-ISE軟體工具設計實作硬體部份,用了297個FPGA的片模組電路(Slice)。

In recent years, people have paid much attention for requirements of better video quality. Since the popularity of flat-panel displays are growing, de-interlacing processing has become a very important technology. In Taiwan, the television programs are still broadcasted with the NTSC interlaced format currently. To let interlaced videos be displayed on the progressive-scan flat-panel displays and get better video quality, we must rely on de-interlacing technologies for video post-processing.
Novel low complexity interpolation (LCI)-based motion adaptive de-interlace technology is proposed for video post-processing. The proposed algorithm uses a new motion adaptive algorithm. In the proposed 4-field motion detection, the proposed detection method improves the shortcoming of the previous detection method. Besides the improvement of the motion detection method, we also classify video data into three parts, which are static, uncertain, and dynamic parts. By using the three-part classification, the video properties can be separated more obviously than the two-part processing algorithms, which only use the partition of static and dynamic parts. Except the static parts are de-interlaced with average interpolation, uncertain and dynamic parts are de-interlaced with the algorithms, which are based on low complexity interpolation. For dynamic parts, we want to expand the detection range, so we develop the LCI method with expansion detection. For uncertain parts, we want to refer the temporal de-interlacing and spatial de-interlacing methods, so we develop the proposed 3D-Median LCI method.
In this thesis, we propose the de-interlacing algorithm which does not use the motion compensation method and the mask scan method, and the proposed method saves computing capacity to achieve high-quality post-processing video as far as it can. Finally, for functional verification with FPGA, we use the SMIMSTM FPGA platform through the Xilinx-ISE software tools for hardware design, and the hardware part uses 297 FPGA slices.
URI: http://hdl.handle.net/11455/8062
其他識別: U0005-1507200815382900
Appears in Collections:電機工程學系所

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