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| 基于有理多项式系数模型的物方面元最小二乘匹配 | |
| 引用本文： | 张过,陈钽,潘红播,江万寿.基于有理多项式系数模型的物方面元最小二乘匹配[J].测绘学报,2011,40(5):592-597. |
| 作者姓名： | 张过 陈钽 潘红播 江万寿 |
| 作者单位： | 1. 武汉大学测绘遥感信息工程国家重点实验室,湖北武汉430079／国家测绘局卫星测绘应用中心,北京100083 2. 武汉大学遥感信息工程学院,湖北武汉,430079 3. 武汉大学测绘遥感信息工程国家重点实验室,湖北武汉,430079 |
| 基金项目： | 国家科技支撑计划(2011BAB01B01);国家自然科学基金(40930532);国家863计划(2008AA121203) |
| 摘 要： | 针对物方面元最小二乘匹配仅适用于单中心投影框幅式成像的匹配制作区域DSM问题，提出基于有理多项式系数（RPC）模型的物方面元最小二乘匹配算法，结合匹配窗口区域内多中心平行投影方式，构建RPC模型下的投影方程，将物方面元最小二乘匹配算法从适用于单中心投影框幅式成像扩展到适用于多中心投影推扫式成像的立体匹配，并用SPOT5-HRG、GeoEye、IKONOS立体影像进行试验验证。试验表明，RPC模型能用于物方面元最小二乘匹配且不损失匹配精度，增加了物方面元最小二乘匹配的应用范围和价值。 |
| 关 键 词： | 影像匹配 最小二乘 有理多项式系数模型 小面元 |
Patch-based Least Squares Image Matching Based on Rational Polynomial Coefficients Model |
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| ZHANG Guo,CHEN Tan,PAN Hongbo,JIANG Wanshou.Patch-based Least Squares Image Matching Based on Rational Polynomial Coefficients Model[J].Acta Geodaetica et Cartographica Sinica,2011,40(5):592-597. | |
| Authors: | ZHANG Guo CHEN Tan PAN Hongbo JIANG Wanshou |
| Institution: | 1.State Key Laboratory for Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430079,China;2.Satellite Surveying and Mapping Application Center,State Bureau of Surveying and Mapping,Beijing 100083,China;3.School of Remote Sensing and Information Engineering,Wuhan University,Wuhan 430079,China |
| Abstract: | Since patch-based least squares image matching only applies to the production of regional DSM that based on single-center projection with frame imaging,patch-based least squares image matching based on rational polynomial coefficients(RPC)model is proposed,with multi-center parallel projection in the matching region and RPC-based projection equation constructed,which extends patch-based least squares image matching from single-center projection with frame imaging to stereo-matching of multi-center projection with push-broom imaging,and the algorithm is proved by the experiment with SPOT5-HRG,GeoEye and IKONOS stereo images.The experimental results show that RPC model can be used in patch-based least squares image matching with high matching accuracy maintained to improve its applications and value. |
| Keywords: | image matching least squares rational polynomial coefficients model small patch |
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