中文摘要：

针对SIFT算法误匹配点多和匹配速度慢的问题,本文提出一种SIFT像素点筛选预处理降维双向匹配方法,在SIFT构造Do G空间前进行像素点筛选预处理,减少无用特征点产生;在特征描述符生成时进行降维处理,减少运算量;最后使用约束配准算法,实现SIFT双向匹配。实验结果表明,本文改进的方法显著地提高了匹配精度和效率。

英文摘要：

Aiming at the problem of many error matching points and slow matching speed of SIFT algorithm, this paper presents a SIFT pixel filter pretreatment dimensionality reduction bidirectional matching method. Before SIFT constructing DoG space, the pixel point needs to preprocess, in order to reduce the useless feature points producing. During feature descriptor generating, the dimensionality needs to be reduced, in order to reduce the amount of computation. Finally, using the constraint registration meth- od, the SIFT bidirectional matching is realized. The experimental results show that the improved method can improve the accuracy and efficiency of matches.