Deinterlacing with motion adaptive vertical temporal filtering

In this paper, we propose a deinterlacing method with motion adaptive vertical temporal filtering, which utilizes the correlations between adjacent frames. In this model, we first interpolate the missing lines of the current frame and adjacent frames by using an intrafield deinterlacing method. Then we compute the pixel differences between the current frame and the adjacent frames. Since the differences between the adjacent frames would show similar patterns, we can use these patterns to improve deinterlacing performance. In other words, instead of performing deinterlacing in the frame domain, we perform the operation in the frame difference domain. Since the proposed method produces good performance in stationary regions, we selectively apply the vertical temporal filter. Then we apply the proposed method iteratively in order to enhance video quality. The proposed method shows low complexity and still produces superior performance. Experimental results show that the proposed method provides noticeable improvements over existing methods in terms of both subjective and objective evaluations.