Fast and efficient intra-frame deinterlacing using observation model based bilateral filter

Recently, a few bilateral filter based interpolation and intraframe deinterlacing algorithms have been proposed, but these algorithms only use prior information (bilateral filter). In this paper, we propose an efficient and fast intra-frame deinterlacing algorithm using an observation model based bilateral filter (using both likelihood and prior information). Our proposed algorithm is also able to use approximated horizontal pixels for the deinterlacing, which results into the better prediction of the edges. From extensive experiments, it is observed that the proposed algorithm has the capability of provide satisfactory results in terms of both objective and subjective quality.