Complexity-Distortion Optimized Motion Estimation Algorithm with Fine-Granular Scalable Complexity

Video encoding now is being implemented in various computing platforms with different computing capability, the requirement on the encoding complexity is also different according to different applications. As the most computation-intensive part of video encoding, the ME (motion estimation) should have a scalable complexity. This paper proposes a ME algorithm with fine-granular scalable complexity, a more important feature of the proposed algorithm is that it seeks for the complexity-distortion optimization. The given computation budget will be allocated to each MB (macroblock) in one frame. Each MB will consume its allocated computation by a hybrid search pattern. Experimental results show that the proposed algorithm can get a better computation-distortion performance than the existing ME algorithms