A General Epipolar-Line Model between Optical and SAR Images and Used in Image Matching

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Studies in Surveying and Mapping Science (SSMS) Volume 2, 2014

A General Epipolar-Line Model between Optical and SAR Images and Used in Image Matching Shuai Xing*1, Qing Xu 1, Pingyuan Cui2, Chaozhen Lan1,2, Pengcheng Li1 1

Zhengzhou Institute of Surveying and Mapping, Zhengzhou, China

2

School of Aerospace Engineering, Beijing Institute of Technology, Bei jing, China

*

xing972403@163.com; xq@szdcec.com; cuipy@bit.edu.cn; lan_cz@163.com; lpclqq@163.com

Abstract The search space and strategy are important for optical and SAR image matching. In this paper a general epipolar-line model has been proposed between linear array push-broom optical and SAR images. Then a dynamic approximate epipolar-line constraint model (DAELCM) has been constructed and used to construct a new image matching algorithm with Harris operator and CRA. Experimental results have shown that the general epipolar-line model is valid and successfully used in optical and SAR image matching, and effectively limits the search space and decreased computation. Keywords Photogrammetry; Match; Accuracy; Optical; SAR

Introduction Neither stereoplotting nor block adjustment will succeed without homologous imag e points in photogrammetry. There are usually two ways to achieve homologous i mage points, stereoscopic measuring an d image matching. Stereoscopic measuring is based on stereoscopic viewing and measuring instrument which costs more time an d labour force. Image matching can automatically acquire homologous points by programs and computers. It is so efficient and automatic that it has been wi dely used in photogrammetry. [1]

Lisa Gottesfeld Brown has divi ded i mage matching into three key problems as feat ure space, si milarity measure, search space an d strategy. He also summarized many image matching algorithms. But now most research concentrates on matching with images acquired by the same sensor at different locations, an d good accuracy an d efficiency h as been achieved. But it is still difficult to match i mages acquired by different sensors, especially optical and SAR i mages. Since imaging mechanisms of optical and SAR images are remarkably different, imag e matching algorithms based on pixel grey value are not suitable. But more imag e matching algorithms based on feature have been used to match optical and SAR i mages because features in different imag es are more stable and easily detect ed. [2]

[3]

O. ThÊpaut et al. an d X. Dai et al. have proposed optical and SAR image matching algorithms based on linear [4] features. Paul Maxwell Dare used area features to match optical and SAR i mages. They focused on the first problem [5] in image matching, feature space. Jordi Inglada et al. have summarized si milarity measures suitable for optical an d SAR image matching and proved cluster reward algorithm (CRA) was the best one. But they all have not considered the third problem, search space an d strategy. Epipolar-line constraint is an excellent search strategy in frame remote sensing image matching, and is well used in many commercial digital photogrammetry softwares. But epipolar-line doesn’t exist in linear array push-broom optical and SAR i mages. So in this paper a dynamic approximate epipolar-line constraint model has been proposed, which has been used to con struct a new matching algorithm with Harris operator and CRA, and successfully used in optical an d SAR i mage matching. Two Imaging Models The approximate epi polar-line relationship between linear array push-broom optical and SAR image is derived from their imaging models, so two imaging models will be introduced first . The Scanning Model The linear array push-broom i mage is acquired with linear sensors by scanning the E arth surface. The relationship

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