快速、鲁棒的图像配准是运动视频处理的基础，也是制约后继应用稳定性及可靠性的关键。针对运动视频中存在的图像平移、旋转、尺度及光照变化，提出一种基于不变特征的快速图像配准算法，包括特征点检测、描述和匹配。首先通过多层箱式滤波器构建图像多尺度空间，并同时考虑质量与空间分布检测特征点；然后用主成分分析法对SIFT(scale invariant feature transform)特征进行降维，用于特征描述；最后根据描述子主成分的差异设计层叠分类器，加速特征匹配。定量分析实验和对视觉监视系统中球形摄像机和无人机航拍视频的实验结果表明，该算法具有良好的匹配性能，为后继运动载台上的运动目标检测、跟踪、分类等处理提供了坚实基础。

Fast and robust image registration is an important research problem in motion video processing. In this paper, we present a novel invariant feature based automatic image registration method to deal with the large image transformation, rotation, scale and illumination changes. The algorithm includes three parts: invariant feature detection, description and matching. First, the multi-scale space of the image is created via a multi-level box filter, and then the feature points are detected in scale space by considering the quality and special distribution simultaneously. Second, we use the Principle Component Analysis to descend dimension of SIFT(Scale invariant feature transform) for feature description. Finally, based on the principle component of the descriptors, a cascade filtering is designed to speed up the feature matching. Experiments with motion videos captured by the dome camera and the Unmanned Aerial Vehicle demonstrate that the proposed algorithm has satisfied performance, and it can provide a solid foundation for further processing such as moving object detection, tracking and classification from moving platform.