De-Interlacing Algorithm Using Spatial-Temporal Correlation-Assisted Motion Estimation

De-interlacing algorithms are used to convert interlaced video into progressive scanning format. The motion-adaptive technique provides acceptable picture quality, but the quality of the motion area still needs to be improved. Among the various de-interlacing techniques, the motion-compensated de-interlacing technique provides the best performance if the estimated motion information is reliable. However, it suffers from inaccurate motion estimation, and the weak error protection thus deteriorates the visual quality. This paper presents a motion-compensated de-interlacing algorithm with highly accurate motion estimation and robust error detection. In order to obtain more accurate motion information, spatial-temporal correlation-assisted motion estimation is proposed. The spatial and temporal correlations among the motion vectors (MVs) are exploited to find the true motion of the object. In order to reject incorrect temporal information, a hierarchical MV reliability verification is provided. The possible defects in both large and small areas can be detected effectively. The experimental results show that the proposed algorithm outperforms existing algorithms and produces high quality de-interlaced results in various video sequences.