The purpose of geometric matching is to extract the geometric transformation parameters between the corresponding images.It is widely used in photogrammetric mapping,deformation detection, and flying platform's posture analysis,etc.In this paper,a new image matching method which is different from the traditional features based image matching algorithm is proposed,it takes all the pixels of the corresponding images to participate the matching procedure and calculate the geometric parameters by least square criterion.The principle of the algorithm,including the gray corresponding equation,the information quantity inequation and procedure of least square solution are expressed.Particularly,the wavelet analysis for gray signal and calculating the information quantity by signal to noise ratio are discussed in detail.For verifying the theory and algorithm,a series of sequential images taking from a video camera mounted on a helicopter are selected for experiment.The results of two typical models according to the relative orientation elements model and parallax grid model are given,and the experimental results show that the proposed algorithm is feasible and effective.The comparison of APM with ordinary features based method by the information quantity inequation is given in the conclusion.%影像几何匹配之目的是从确定对应的影像中提取其间的几何转换参数,在摄影测量测图、变形物面监测和飞行平台动态性能分析等方面有许多实用需求.不同于普遍悉知的特征点影像匹配算法,本文研究的算法是把对应影像内的全部像元素参加匹配运算,从而按最小二乘准则求解对应影像间的几何转换参数值.文中阐述了算法原理,包括灰度对应方程、信息量不等式及最小二乘求解方法,尤其是详细探讨了灰度信息的小波分析及由信噪比计算信息量的方法.为验证本文的理论和方法,采用了直升机载视频相机的序列影像进行了试验,给出了相对定向元素和视差格网的两种解算结果.最后给出了本文方法与传统特征点匹配方法可利用信息量不等式进行对比分析的结论.
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