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A motion-compensated deinterlacing scheme based on hierarchical motion analysis is presented. According to deinterlacing steps, our contribution can be divided into four parts: motion estimation, motion state analysis, motion consistency analysis, and finer-grained interpolation. In motion estimation, we introduce a Gaussian noise model for choosing the best motion vector for each block, and make...
Because of its ability to preserve signal edges while filtering out impulsive noises, median filtering is widely used in signal processing applications, e.g. deinterlacing. An edge-based median filtering (EMF) algorithm is proposed for adaptive deinterlacing. A criterion of motion vector reliability (MVR) is also introduced for better interpolation. For each motion compensated block, two motion vectors...
In this paper, we propose a novel hybrid de-interlacing algorithm, which effectively combines two motion-compensated (MC) de-interlacing techniques: MC median filtering (MCMF) and adaptive recursive (AR) with one spatial approach: line averaging (LA). Despite of its drawbacks, AR is one of the best methods nowadays. MCMF helps reduce flickers and LA is very robust to erroneous motion vectors. The...
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