运动估计算法预测搜索起始点

摘要

高精度的预测搜索起始点方法可以减少运动估计算法的搜索点数,提高搜索速度和精度.对中值,均值,左块,SAD比较等方法进行了理论介绍和实验分析,提出一种新的预测搜索起始点方法.该方法足利用相邻块运动矢量的相关性和运动矢最的偏向分布特征给相邻块分配不同的权重来预测搜索起始点.实验结果表明对不同种类的标准测试序列新方法比其它方法能够减少更多的搜索点数,减少搜索点数的总数达到29.24且PSNR提高1.71dB.%High precision of the prediction of searching initial point can reduce the number of search points to improve the search speed and search precision. The median, the mean, the left block, the SAD (Sum of Absolute Difference)comparison and other methods of the prediction of searching initial point were theoretically and experimentally analysised. And according to The correlation of adjacently blocks' motion vectors and the characteristic of the center-biased characteristic of motion vectors in image sequences, a novel method of the prediction of searching initial point was proposed. The novel method assigns different weights to the adjacent blocks. Experimental results show that the novel method gains better reduction(29.24) in the number of searching point over the different kinds of criterion testing video sequence and impoves 1.71dB in peak signal to noise Ratio(PSNR).