Efficient adaptive deinterlacing algorithm with awareness of closeness and similarity

Abstract

We introduces an efficient intra-field deinterlacing algorithm while considering both closeness and similarity between the interpolated pixel and the neighbor pixels. Instead of estimating the edge orientations via limited candidate directions as previous intra-field deinterlacing methods, we propose an adaptive spatial locality- and similarity-based deinterlacing method. Many deinterlacing methods described in the literature only consider the similarity between neighbor pixels and interpolated pixels; however, awareness of distance correlation and spatial locality has not yet been studied. Experimental results indicate that the proposed scheme outperforms a number of existing approaches, in terms of both the objective and subjective performance.