Block-based motion estimation is widely used in video compression for exploitation of video temporal redundancy. Although effective, the process is arguably the most computationally intensive step in a typical video encoder. To speed up the process, a large number of fast block-matching algorithms (BMAs) have been proposed for motion estimation by limiting the number of search locations or simplifying the measure of match between the two blocks under comparison. In this paper we propose a new BMA that measures the match by using such block features as block mean and block variance, quantities that can be easily computed from integral frame attributes. Experimental results show that the proposed BMA can reduce notably the computational load and achieve compression performance very close to that of existing BMAs using conventional block-matching measures.
展开▼
