A Hybrid Adaptive Search Algorithm for Fast Block Motion Estimation

This paper proposes a hybrid adaptive search algorithm (HASA) for block-based motion estimation. The proposed algorithm exploits the correlation between the block distortion measure (BDM) of the search origin (0,O) and its displacement from the motion vector to predict the range of motion. Based on the predicted motion type and the center-biased statistical distribution of motion vectors in low bit rate applications, one of the two block matching algorithms: Four-step search (4SS) or center-biased orthogonal search (CBOSA) is employed to find the motion vector. Experimental results show that HASA outperforms the well-known three-step search (3SS) and new three-step search (N3SS) in terms of number of search points while maintains acceptable mean square errors (MSEs). Moreover, it could effectively predict the stationary motion so as to stop the search at the first search point. The proposed algorithm is very suitable for low bit rate applications using software based video encoder.