基于CSS角点提取的红外与可见光图像匹配算法

针对红外与可见光图像中特征点匹配的难题,提出了一种基于曲率尺度空间（curvature scale space,CSS)角点提取的特征点匹配算法。首先采用基于曲率尺度空间的角点检测算法进行特征点提取；其次利用三维二次函数剔除低对比度的特征点；然后以特征点所在曲线的法线作为主方向,避免了图像的旋转代价；再通过计算构建特征点邻域的梯度方向在［0,π)范围的分布直方图,计算其统计特征并构造一个64维的特征点描述符,并进行归一化；最后采用最近邻算法实现直线匹配。实验结果表明,该算法能够有效地实现对红外与可见光图像特征点的精确匹配。

Matching algorithm for IR/visible images based on CSS corner extraction

A point matching algorithm based on the curvature scale space(CSS) corner extraction is proposed to resolve the problem of point matching in the infrared(IR) and visible images.Firstly,the candidate feature points are extracted with a CSS corner detector.Secondly,the low contrast points are rejected by the 3D quadratic function.And thirdly,the normal direction of each feature point on the curve is adopted as the main direction of the point,thus the rotation of images is avoided.Fourthly,the gradient histogr...