Rough sets attributes reduction based expert system in interlaced video sequences

A deinterlacing algorithm that is based on rough sets theory is researched and applied in this paper. The fundamental concepts of rough sets, with upper and lower approximations, offer a powerful means of representing uncertain boundary regions in image processing. However, there are a few studies that discuss the effectiveness of the rough sets concept in the field of engineering. Moreover, the studies involving deinterlacing systems that are based on rough sets have not been proposed yet. Thus, this paper proposes a deinterlacing method that will reliably confirm that the method being tested is the most suitable for the sequence, with almost perfect reliability. This proposed deinterlacing approach employs a size reduction of the database system, keeping only the essential information for the process. Decision making and interpolation results are presented. The results of computer simulations show that the proposed method outperforms a number of methods presented in the literature

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