Title :
A Linear Prediction Based Fractional-Pixel Motion Estimation Algorithm
Author :
Ng, Ka-Ho ; Po, Lai-Man ; Li, Shen-Yuan ; Wong, Ka-Man ; Wang, Li-Ping
Author_Institution :
Dept. of Electron. Eng., City Univ. of Hong Kong, Hong Kong, China
Abstract :
In modern video coding standards, for example H.264, fractional-pixel motion estimation (ME) is implemented. Many fast integer-pixel ME algorithms have been developed to reduce the computational complexity of integer-pixel ME. With these advancements, fractional-pixel ME becomes the new bottleneck in the implementation of video encoders. For example, the conventional hierarchical fractional-pixel search (HFPS) at quarter-pixel accuracy requires computing the distortions of at least 16 fractional-pixel positions. This computation is comparable to or even higher than advanced fast integer-pixel ME process. Fast fractional-pixel ME algorithms were therefore developed, in which initial search point is first predicted before applying fast refinement search. Parabolic error surface model and fractional-pixel motion vector information of neighboring blocks are commonly used for initial search point prediction but they have problems of unsolvable solution and uncorrelated motion vectors, respectively. To tackle these problems, a center-biased fast fractional-pixel ME algorithm using linear prediction based search with intrinsic center-biased characteristic is developed in this paper. Experimental results show that the proposed algorithm is fast and robust.
Keywords :
computational complexity; error analysis; linear predictive coding; motion estimation; search problems; video coding; H.264 coding; center biased fast integer pixel ME algorithm; computational complexity; hierarchical fractional pixel search; linear prediction based fractional-pixel motion estimation algorithm; motion vector information; parabolic error surface model; quarter pixel accuracy; search point prediction; video coding standard; video encoder; Equations; Mathematical model; Motion estimation; PSNR; Pixel; Prediction algorithms; Predictive models;
Conference_Titel :
Multimedia and Ubiquitous Engineering (MUE), 2010 4th International Conference on
Conference_Location :
Cebu
Print_ISBN :
978-1-4244-7563-6
DOI :
10.1109/MUE.2010.5575049