全部像元参加的影像几何匹配算法

杨应; 林宗坚

doi:10.11947/j.AGCS.2017.20160368

测绘学报 >

2017 , Vol. 46 >Issue 5: 573 - 582

DOI: https://doi.org/10.11947/j.AGCS.2017.20160368

摄影测量学与遥感

全部像元参加的影像几何匹配算法

杨应 ,
林宗坚

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1. 武汉大学遥感信息工程学院, 湖北武汉 430079;
2. 中国测绘科学研究院, 北京 100039

杨应(1986-),男,博士生,研究方向为摄影测量与遥感。E-mail:yingy@whu.edu.cn

收稿日期: 2016-07-28

修回日期: 2017-03-01

网络出版日期: 2017-06-05

基金资助

国家自然科学基金（41371425）

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All-pixels Participated Image Matching Algorithm for Geometric Solution

YANG Ying ,
LIN Zongjian

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1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China;
2. Chinese Academy of Surveying and Mapping, Beijing 100039, China

Received date: 2016-07-28

Revised date: 2017-03-01

Online published: 2017-06-05

Supported by

The National Natural Science Foundation of China (No.41371425)

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摘要

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。

关键词： 影像几何匹配; 信息论; 小波分析; 灰度对应方程; 信息量不等式; 全部像元素匹配

本文引用格式

杨应 , 林宗坚 . 全部像元参加的影像几何匹配算法[J]. 测绘学报, 2017 , 46(5) : 573 -582 . DOI: 10.11947/j.AGCS.2017.20160368

Abstract

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.

Key words： geometric image matching; information theory; wavelet analysis; gray corresponding equation; Information quantity inequation; all-pixels participated matching

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