Báo Cáo Báo cáo hóa học Research Article A Motion-Adaptive Deinterlacer via Hybrid Motion Detection and Edge

Báo cáo hóa học: Research Article A Motion-Adaptive Deinterlacer via Hybrid Motion Detection and Edge-Pattern Recognition
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Research Article
AMotion-Adaptive Deinterlacer via HybridMotion Detection
and Edge-Pattern Recognition
Gwo Giun Lee,
1 Ming-JiunWang,
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-JiunWang, <a class="__cf_email__" href="http://www.cloudflare.com/email-protection" data-cfemail="e08ed2d8d9d4d1d5d5a083838d81898cce8e838b95ce858495ce9497">[email protected]<script type="text/javascript">
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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 contentsmakes the processing of assortedmotion, edges, textures, and the combination of themvery 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, predict-
ing 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 unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.