基于改进的尺度不变特征变换特征点匹配的电子稳像算法

Electronic image stabilization algorithm using improved scale invariant feature transform

针对传统尺度不变特征变换(SIFT)算法运算量大的问题,提出了一种改进的SIFT特征点匹配算法。首先介绍了SIFT特征向量的提取过程,并对算法进行了改进,在单尺度空间内提取目标的关键点,并形成34维特征向量,来代替传统SIFT算法生成的128维特征向量,使算法的实时性得到较大的提高,同时又保持了配准精度,最后将提出的改进SIFT特征应用于电子稳像中的全局运动估计中,并通过实验验证了算法的性能。

In order to satisfy the real-time requirement of image stabilization, this paper proposed a new matching method based on the improved Scale Invariant Feature Transform （SIFT） features. The presented method extract the key points of the target within the space of a single scale, and the formation of 34-dimensional feature vector, instead of the traditional SIFT algorithm to generate the 128-dimensional feature vector, so that the real-time of the algorithm was greatly improved, while maintaining the registration accuracy. At last, the improved SIFT features were used in the global motion estimation of the electronic image stabilization. The experiments verified the performance of the algorithm.