Abstract
Video deinterlacing is a technique wherein the interlaced video format is converted into progressive scan format for nowadays display devices. In this paper a spatial saliency-guided motion compensated deinterlacing method is proposed: our algorithm classifies the field according to its texture and viewer’s region of interest and adapts the motion estimation and compensation, as well as the saliency-guided interpolation in order to ensure high quality frame reconstruction. The experimental results show significant improvement of the proposed method over classical motion compensated and adaptive deinterlacing techniques.
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Trocan, M., Coudoux, FX. (2015). Saliency-Guided Video Deinterlacing. In: Núñez, M., Nguyen, N., Camacho, D., Trawiński, B. (eds) Computational Collective Intelligence. Lecture Notes in Computer Science(), vol 9330. Springer, Cham. https://doi.org/10.1007/978-3-319-24306-1_3
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DOI: https://doi.org/10.1007/978-3-319-24306-1_3
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