<title>Fast motion vector estimation by using spatiotemporal correlation of motion field</title>

Abstract

Motion vector (MV) estimation plays an important role in motion compensated video coding. In this research, we first examine a stochastic MV model which enables us to exploit the strong correlation of MVs in both spatial and temporal domains in a given image sequence. Then, a new fast stochastic block matching algorithm (SBMA) is proposed. The basic idea is to select a set of good MV candidates and choose from them the one which satisfies a certain spatio-temporal correlation rule. The proposed algorithm reduces matching operations to about 2% of that of the full block matching algorithm (FBMA) with only 2% increase of the sum of absolute difference (SAD) in motion compensated residuals. The excellent performance of the new algorithm is supported by extensive experimental results.