A motion adaptive deinterlacing algorithm using improved motion detection

Abstract

In this paper, a motion adaptive deinterlacing algorithm is proposed. It consists of three parts: (1) modified edge-based line average, (2) pixel-based consequent five-field motion detection, and (3) block-based local characteristic for detecting true motion and calculating the motion intensity by using an improved method which is able to detect the inner part of moving objects precisely as well as to reduce the risk of false detection caused by intrinsic noises in the image. Depending on the detected motion activity level, it combines spatial and temporal methods with weighting factor. Simulations conducted on several video sequences indicate that the performance of the proposed method is superior to the conventional methods in terms of both subjective and objective video quality.