An Optimal Fast Full Search Motion Estimation and Suboptimal Motion Estimation Algorithms

The new fast full search motion estimation algorithm for optimal motion estimation is proposed in this paper. The Fast Computing Method (FCM) which calculates the tighter boundaries faster by exploiting the computational redundancy and the Best Initial Matching Error Predictive Method (BIMEPM) which predicts the best initial matching error that enables the early rejection of highly impossible candidate blocks are presented in this paper. The proposed algorithm provides the optimal solution with fewer computations by utilizing these two methods FCM and BIMEPM. Experimental results show that the proposed new fast full search motion estimation algorithm performs better than other previous optimal motion estimation algorithms such as Successive Elimination Algorithm (SEA), Multilevel Successive Elimination Algorithm (MSEA) and Fine Granularity Successive Elimination (FGSE) on several video sequences. The operation number for this proposed algorithm is reduced down to 1/52 of Full Search (FS). But MSEA and FGSE algorithms can reduce computations by 1/40 and 1/42 of FS. Finally, the proposed new fast full search motion estimation algorithm is modified to sub optimal motion estimation algorithm introducing only a small average PSNR drop of around 0.2dB but achieves very fast computational speed. The superior performance of this sub optimal motion estimation algorithm over some fast motion estimation algorithms is also proved experimentally. General Terms Video coding, video processing.