Title :
Fast sub-pel motion vector prediction via block classification
Author :
Zhang, Qi ; Dai, Yunyang ; Kuo, C. C Jay
Author_Institution :
Ming Hsieh Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
Abstract :
A technique to predict the optimal sub-pel motion vector (MV) position based on integer-pel MVs is investigated in this work. Although it is possible to find the optimal MV position by fitting a local error surface using integer-pel MVs, the minimum of the error surface may fall outside of the region of interest. By analyzing the behavior of the error surface, we propose a classification scheme that divides blocks into regular and irregular types. For a regular block, we adopt the traditional error surface model and solve its minimum as the predicted sub-pel MV position. For an irregular block, we developed a novel prediction scheme to predict the optimal sub-pel MV position. Experimental results are given to show the low complexity and good RD performance of the proposed sub-pel MV prediction scheme.
Keywords :
motion estimation; pattern classification; block classification; classification scheme; error surface model; subpel motion vector prediction; Automatic voltage control; Image processing; Motion estimation; Performance analysis; Predictive models; Rate-distortion; Redundancy; Signal processing; Surface fitting; Video coding; error surface modeling; fast motion estimation; motion vector prediction; sub-pel motion search;
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2009.5414607