Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/8436
標題: 使用邊緣偵測器之低複雜度且邊緣保存的二維解交錯演算法
A low-complexity and edge-preservation 2-D de-interlacing algorithm with edge detector
作者: 張碧倉
Chang, Pi-Tsang
關鍵字: de-interlace;解交錯;low-complexity;二維;低複雜度
出版社: 電機工程學系所
引用: [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] S. C. Tai, C. S. Yu, and F. J. Chang, 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. [3] 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. [4] Chung J. Kuo, Ching Liao, and Ching C. Lin “Adaptive Interpolation Technique for Scanning Rate Conversion” IEEE Transactions on Circuits and Systems for Video Technology , Vol.6(No.3),1996 [5] Ching-Ting Hsu, Mei-Juan Chen and Chin-Hui Huang,”High Performance Spatial -Temporal De-interlacing Technique Using Interfield Information” IEEE Trans. on Consumer Electronics, Volume 2, Page, Nov. 2004. [6] Qinggang Zhou, Clyde H. Nagakura, Sheng-Fu Wu, Andrew K. Chan, “Deinterlacer using both low angle and high angle spatial interpolation description”;US patent 7202908, Aug 2007. [7] Zhongde Wang, Dennis Morel, “Weighted absolute difference based deinterlace method and apparatus”, US Patent 7515205, Dec.2006 [8] Yu-Lin Chang, Shyh-Feng Lin, and Liang-Gee Chen,”Extense intelligent edge-based line average with its implementation and test method”,Page2-341,IEEE 2004. [9] T. Doyle and M. Looymans, “progressive scan conversion using edge information”, in Proc 3rd Int.Workshop sigal processing of HDTV, Aug. 1989, PP.711-721. [10] G. de Haan and E.B.Bellers,”Deinterlacing-an overview,”Proceedings of the IEEE,Vol. 86, Issue 9,PP. 1839-1857,1998 l [11] G. de Haan and E.B.Bellers,”Deinterlacing of Video Data,”IEEE Transaction on Consumer Electronics.Vol.43, Issue3, pp.819-825,August 1997. [12] Keith Jack,”Video Demystified,3rd ed.”, HARRIES,2001. [13] M.H. Lee, J.H. Kim, J.S. Lee, K.K.Ryu and D. Song, “ A new algorithm for interlaced to progressive scan conversion based on directional correlations and its IC design”, IEEE Trans. on Consumer Electronics, vol. 40, n. 2, pp. 119-129, May 1994. [14] H. Mahvash M., J.M. P. Langlois, and Y. Savaria, “A Threshold-Based De-Interlacing Algorithm Using Motion Compensation and Directional Interpolation,” IEEE ICECS, Nice France, Dec. 2006. [15] Dongil Han, Chang-Yong Shin, Seung-Jong Choi and Jong-Seok Park,” A Motion Adaptive 3-D De-interlacing Algorithm Based on the Brightness Profile Pattern Difference,” IEEE consumer electronics , June 1999.
摘要: 
爲了降低電視廣播時的頻寬,電視系統採用交錯式的影像訊號來傳送,但是平面顯示器無法直接將交錯式訊號直接播放,必須經過解交錯的處理,將交錯式訊號還原為循序式訊號,而解交錯演算法的好壞,將直接影響顯示器的畫質。
現今解交錯的演算法雖可以有效的改善影像品質,但影像品質仍然受到水平邊緣場景影響,且現今使用的解交錯演算法並沒有針對水平邊緣的畫面作特別的技術處理,容易發生水平邊緣模糊現象、鋸齒現象和爆點現象。在這篇論文中,我們提出一個有效的邊緣偵測器,來將等待插補的影像邊緣區分為斜邊、近似水平邊緣與水平邊緣等三種狀態來處理,而且掃描線增加為三條,與先前相關的四條掃描線演算法來比較,大幅改善了影像品質。
本論文所提出的低複雜度解交錯演算法,是在只有參考單張圖片資訊的情況下,盡量去節省運算量以達到高品質的解交錯影像結果。我們使用Visual C++做演算法模擬驗證的工具,評估其峰值信號對雜訊比(PSNR),並且比較不同解交錯演算法的中央處理器(CPU)所需運作時間; 而模擬用的個人電腦規格為使用Intel Pentium M 1.73 GHz 中央處理器,記憶體空間為1Gb RAM。

In order to reduce the bandwidth for broadcasting the traditional TV signals, the interlaced video signals are used to transmit, but the flat-panel displays can not directly display the interlaced signals. Thus, the broadcast signals must pass through the de-interlacing processing, and the interlaced signals can be converted to the progressive signals. The performance of the de-interlacing algorithms will directly affect the visual quality on progressive displays.
Although the present de-interlacing algorithms can effectively improve the image visual quality, the image quality is still affected by the de-interlacing effect of the horizontal edge. The de-interlacing algorithms used recently have not paid the enough attentions to process the horizontal edge yet, and it will result in the ambiguity phenomenon, saw-tooth phenomenon, and the explosion point phenomenon at the horizontal edges. In this paper, we propose an effective edge detector to divide the interpolated edge pixel into three categories, which are the oblique edge, the near horizontal edge, and the horizontal edge, and the number of the used scan lines is increased to three. Compared with the previous four scan-line algorithm, our method significantly improves the image visual quality.
In this paper, we propose a low complexity de-interlacing algorithm, which only refers to the information on a single input field. We reduce the computations as far as possible and try to achieve high-quality de-interlacing image results simultaneously. We use Visual C ++ software as tools to simulate and verify the algorithms, obtain the peak signal to noise ratio (PSNR), and compare our design with different de-interlacing algorithms. The required central processing unit (CPU) times for different de-interlacing algorithms are also shown. The simulation platform is a personal computer and its specifications are that the Intel Pentium M CPU works up to 1.73 GHz, and the memory space uses 1Gb RAM
URI: http://hdl.handle.net/11455/8436
其他識別: U0005-0502201008584900
Appears in Collections:電機工程學系所

Show full item record
 

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.