改进的SIFT特征匹配算法

针对SIFT特征匹配算法在特征空间中进行历遍搜索,匹配速度慢的问题,提出一种金字塔层间匹配算法。首先,根据特征点所处金字塔层不同将特征点划分为不同的集合,其次,选择待配准图像金字塔中某一层集合,在基准图像金字塔中寻找相似层,并确定待配准图像金字塔与基准图像金字塔层之间的相似关系,最后,在相似层之间寻找匹配点。待配准图像中的选择层集合由金字塔底层到顶层,寻找相似层所用时间依次缩短。与原算法相比,该算法具有相同的旋转稳定性。将该算法与原算法分别应用实际图像配准中,结果表明:可见光图像配准中,匹配速度提高了3.2倍,正确匹配率提高了10.3％,红外图像配准中,匹配速度提高1.4倍,正确匹配率达到100％。

An Improved Algorithm for SIFT Feature Matching

Aimed at the slow matching speed of SIFT feature matching method in searching the whole database of feature points for matching points, an improved matching method of searching between the layers of the pyramid is proposed for improving the speed of SIFT matching. First, according to the feature points in different layers of the pyramid, the feature points are divided into different sets. Then a layer set in the input image pyramid is chosen to search for the similar layer in the template image pyramids, and then the similarity between input image pyramid and the template pyramid is determined. Finally, the matches are found between the similar layers. The chosen layer in the input image pyramid is from the bottom of the pyramid to the top of the pyramid. By so doing, the time of searching for similar layer is shorten. Compared with the original algorithm, this algorithm has the same rotational stability. This algorithm and the original algorithm are applied to the actual image registration respectively, the results show that the matching speed is 3.2 times as fast as the original matching speed and the correct matching rate is increased by 10.3% in visual image registration. In infrared image registration the matching speed is 1.4 times as fast as the original matching speed and the correct matching rate reaches 100%.