Multi-Pass and Frame Parallel Algorithms of Motion Estimation in H.264/AVC for Generic GPU

In this paper, multi-pass and frame parallel algorithms are proposed to accelerate various motion estimation (ME) tools in H. 264 with the graphics processing unit (GPU). By the multi-pass method to unroll and rearrange the multiple nested loops, the integer-pel ME can be implemented with two-pass process on GPU. Moreover, fractional ME needs six passes for frame interpolation with six-tap filter and motion vector refinement. Motion estimation with multiple reference frames can be implemented with two-pass process with frame-level parallel scheme by use of SIMD vector operations of GPU. Experimental results show that, compared to implementations with only CPU, about 6 times to 56 times speed-up can be achieved for different ME algorithms.