Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A Motion-Adaptive Deinterlacer via Hybrid Motion Detection and Edge-Pattern Recognition | Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2008 Article ID 741290 10 pages doi 2008 741290 Research Article A Motion-Adaptive Deinterlacer via Hybrid Motion Detection and Edge-Pattern Recognition Gwo Giun Lee 1 Ming-Jiun Wang 1 Hsin-Te Li 2 and He-Yuan Lin1 1 Department of Electrical Engineering National Cheng Kung University 1 Ta-Hsueh Road Tainan 701 Taiwan 2 Sunplus Technology Company Ltd 19 Chuangsin 1st Road Hsinchu 300 Taiwan Correspondence should be addressed to Ming-Jiun Wang n2894155@ Received 31 March 2007 Revised 25 August 2007 Accepted 13 January 2008 Recommended by J. Konrad A novel motion-adaptive deinterlacing algorithm with edge-pattern recognition and hybrid motion detection is introduced. The great variety of video contents makes the processing of assorted motion edges textures and the combination of them very difficult with a single algorithm. The edge-pattern recognition algorithm introduced in this paper exhibits the flexibility in processing both textures and edges which need to be separately accomplished by line average and edge-based line average before. Moreover predicting the neighboring pixels for pattern analysis and interpolation further enhances the adaptability of the edge-pattern recognition unit when motion detection is incorporated. Our hybrid motion detection features accurate detection of fast and slow motion in interlaced video and also the motion with edges. Using only three fields for detection also renders higher temporal correlation for interpolation. The better performance of our deinterlacing algorithm with higher content-adaptability and less memory cost than the state-of-the-art 4-field motion detection algorithms can be seen from the subjective and objective experimental results of the CIF and PAL video sequences. Copyright 2008 Gwo Giun Lee et al. This is an open access article distributed under the Creative Commons Attribution License which permits .
