Weighted interpolation filter incorporating local region statistics

Abstract

We propose a local region statistics-based weighted interpolation filter for intrafield deinterlacing. The proposed algorithm consists of three steps: first, we preinterpolate the missing line with an efficient interpolation filter in the working window. Then, we calculate the coefficients of the center-weighted interpolation filter by exploiting local statistics, namely the center-weighted mean, the center-weighted variance, and the closeness of the neighboring pixels. In the last step, we interpolate the missing line using the proposed filter. Experimental results show that the proposed algorithm provides superior performances in terms of both objective and subjective image qualities than the existing algorithm.