A spatio-temporal recursive search based prediction scheme for efficient multi-frame and bidirectional motion estimation

In this paper a new multi-frame/bidirectional motion estimation algorithm based on the concept of recursive-search in spatial and temporal space is proposed that effectively minimizes the number of candidate motion vectors in the prediction set. The algorithm is extremely computationally light compared to full search and outperforms existing fast approaches. The algorithm can operate effectively on reference frames that may be chosen to be consecutive or temporally separated. The average Peak Signal-to-Noise Ratio (PSNR) performance and compression efficiency is virtually not compromised and very close to full search. Results based on a number of video sequences and on different GOP (Group of Pictures) structures are presented to clearly demonstrate the benefits of the proposed motion estimation technique.