Application of Bayesian belief network in reliable analysis for video deinterlacing

  • Jeon, Gwanggil
  • Falcon, Rafael
  • Kim, Donghyung
  • Lee, Rokkyu
  • Jeong, Jechang
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초록

In this paper, we illustrate that Bayesian networks (BNs), which are also known as belief networks, are well-suited for image processing. We provide case studies on video deinterlacing methods. The proposed efforts at modeling weight measuring process involved in weight assignment of conventional deinterlacing methods that are commonly used for industrial world. Using probabilistic BNs, the system determines the weights and interpolates the missing pixels robustly. The results of empirical trial show that the proposed system can deal successfully with several types of images containing motion or detail.(1).

키워드

Bayesian networksdeinterlacingexpert systemsreasoning under uncertainty modelingstatistical inferenceBayesian networksInference enginesInterpolationMotion compensationPixelsProbability
제목
Application of Bayesian belief network in reliable analysis for video deinterlacing
저자
Jeon, GwanggilFalcon, RafaelKim, DonghyungLee, RokkyuJeong, Jechang
DOI
10.1109/TCE.2008.4470034
발행일
2008-02
유형
Article
저널명
IEEE Transactions on Consumer Electronics
54
1
페이지
123 ~ 130