Block-based motion estimation using the pixelwise classification of the motion compensation error

Abstract

In this paper, we propose block-based motion estimation (ME) algorithms based on the pixelwise classification of two different motion compensation (MC) errors: 1) displaced frame difference (DFD) and 2) brightness constraint constancy term (BCCT). Block-based ME has drawbacks such as unreliable motion vectors (MVs) and blocking artifacts, especially in object boundaries. The proposed block matching algorithm (BMA)-based methods attempt to reduce artifacts in object-boundary blocks caused by incorrect assumption of a single rigid (translational) motion. They yield more appropriate MVs in boundary blocks under the assumption that there exist up to three nonoverlapping regions with different motions. The proposed algorithms also reduce the blocking artifact in the conventional BMA, in which the overlapped block motion compensation (OBMC) is employed especially to the selected regions to prevent the degradation of details. Experimental results with several test sequences show the effectiveness of the proposed algorithms.