Multi-Scale PIIFD for Registration of Multi-Source Remote Sensing Images

This paper aims at providing multi-source remote sensing images registered in geometric space for image fusion.Focusing on the characteristics and differences of multi-source remote sensing images,a feature-based registration algorithm is implemented.The key technologies include image scale-space for implementing multi-scale properties,Harris corner detection for keypoints extraction,and partial intensity invariant feature descriptor(PIIFD)for keypoints description.Eventually,a multi-scale Harris-PIIFD image registration algorithm framework is proposed.The experimental results of fifteen sets of representative real data show that the algorithm has excellent,stable performance in multi-source remote sensing image registration,and can achieve accurate spatial alignment,which has strong practical application value and certain generalization ability.

基于NSCT域FAST角点检测的电气设备红外与可见光图像配准

针对电气设备在线监测系统中红外与可见光图像配准问题,提出了基于非下采样轮廓波变换(Non-Subsampled Contourlet Transform,NSCT)域改进的加速分割检测特征(Features from Accelerated Segment Test,FAST)提取的图像配准方法。首先采用灰度均衡技术对原始图像进行图像增强;再通过一级NSCT变换得到红外与可见光的低频子带图像;然后对低频子带图像利用FAST角点检测以及局域强度不变特征描述符(Partially Intensity In-variant Feature Descriptor,PIIFD)得到特征描述点对;最后,利用最近邻距离比率法及随机抽样一致性算法(Random Sample Consensus,RANSAC)得到精匹配点对,进而计算仿射变换参数。实验结果表明,相比传统的PIIFD配准算法,该方法的特征点正确匹配率提高了2. 52%,配准均方根误差降低11. 58%。