基于SIFT算法的红外图像拼接方法改进

针对红外图像拼接误匹配点过多、耗时过长等问题, 对基于SIFT算法的红外图像拼接方法进行改进. 首先利用高斯差分金字塔建立尺度空间, 然后利用FAST算法对高斯差分金字塔图像进行特征点提取, 提高了算法运行效率, 随后以特征向量的欧式距离作为特征点的相似性度量, 从而找到初始匹配点对, 并利用结合了方向一致性判断的Ransac算法剔除错误匹配点对, 最后用加权平衡算法实现图像的快速融合. 通过红外人物图像拼接实验, 证明改进后的算法在旋转、缩放、光照等情况下更稳定、效率更高, 有较大的理论和应用价值.

Improved Algorithm Based on SIFT Infrared Image Stitching Algorithm

To solve the problems of long registration time and many wrong registrations in using the infrared image stitching algorithm. This paper improves the infrared image stitching algorithm which based on SIFT algorithm. Firstly, the improved algorithm uses the Gaussian difference pyramid to establish the scale space. Secondly, this algorithm uses FAST algorithm to extract the feature points from the Gaussian pyramid difference images. In order to find the initial matching point pairs, the method of this paper calculates the feature vectors distance to measure the similarity of feature points. Thirdly, RANSAC algorithm and direction consistency method are used to remove the wrong matching point pairs. Finally, this algorithm uses weighted average method to mosaic images. The result of the infrared image mosaic experiments shows that the improved method is more stable and more rapid.