在大规模源图像上进行图像匹配时，最佳匹配点的搜索策略是匹配算法时间性能的决定因素，设计

高效匹配搜索策略是提高算法性能的关键。为了减少搜索时间和提高匹配实时性，本文基于匹配源图像划

分和量子遗传算法基本原理，提出了面向大规模源图像匹配的目标淘汰搜索策略TESS。TESS将基于整幅源

图像的全空间随机搜索的过程变成基于各个子图像的子空间并行搜索和逐步淘汰的过程，实现了匹配区域

粗定位与匹配点精搜索的有效结合，从而大大缩短了最佳匹配点的搜索时间。实验结果表明，TESS搜索策

略带来了匹配速度的极大提高，且时间加速比随匹配源图像规模的增大而增大。

When the source image scale is large enough,the search time will be excessively

long if the entire space searching on the source image is carried on. In order to decrease

the search time and  increase the realtime matching capability,a target elimination search

strategy (TESS) is proposed based on the source image division and the basic principle of

QGA. Through changing the random searching process in the entire space to the parallel

searching in each subspace and the subspaces gradually,TESS combines the matching region

roughestimating with the optimal matching point finesearching effectively,so the search

time  decreases enormously. The experimental results indicate that TESS makes the matching

efficiency is improved enormously and  the time speedup increases with the  source image

scale increase.