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1.信息工程大学 地理空间信息学院, 河南 郑州 450001
2.地理信息工程国家重点实验室, 陕西 西安 710054
[ "郭文月(1990-), 女, 辽宁辽阳人, 博士研究生, 2012年、2015于信息工程大学分别获得学士、硕士学位, 主要从事数字图像处理、时空数据挖掘等方面的研究。E-mail:guowyer@163.com" ]
余岸竹(1989-), 男, 湖北罗田人, 博士研究生, 2011年、2011年于信息工程大学分别获得学士、硕士学位, 主要从事数字图像处理、数字摄影测量方面的研究。E-mail:anzhu_yu@126.comE-mail:anzhu_yu@126.com
[ "刘海砚(1971-),男,河北唐山人,博士,教授,博士生导师,1993年、1999年、2002年于解放军测绘学院分别获得学士、硕士、博士学位,主要从事数字地图制图、地理信息工程等方面的研究。E-mail:liu2000@vip.sina.com" ]
[ "姜挺(1963-),男,山东即墨人,博士,教授,博士生导师,1983年、1987年于解放军测绘学院分别获得学士、硕士学位,1997年于德国慕尼黑国防军大学获得博士学位,主要从事数字摄影测量、遥感图像处理、高分辨率对地观测" ]
收稿日期:2016-07-13,
录用日期:2016-9-10,
纸质出版日期:2017-01-25
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郭文月, 余岸竹, 刘海砚, 等. 正则化总体最小二乘用于光学线阵遥感影像定位[J]. Editorial Office of Optics and Precision Engineeri, 2017,25(1):236-244.
Wen-yue GUO, An-zhu YU, Hai-yan LIU, et al. Regularized total least squares used in remote sensing image positioning of optical line array[J]. Optics and precision engineering, 2017, 25(1): 236-244.
郭文月, 余岸竹, 刘海砚, 等. 正则化总体最小二乘用于光学线阵遥感影像定位[J]. Editorial Office of Optics and Precision Engineeri, 2017,25(1):236-244. DOI: 10.3788/OPE.20172501.0236.
Wen-yue GUO, An-zhu YU, Hai-yan LIU, et al. Regularized total least squares used in remote sensing image positioning of optical line array[J]. Optics and precision engineering, 2017, 25(1): 236-244. DOI: 10.3788/OPE.20172501.0236.
针对光学线阵遥感影像几何定位中,系统误差改正参数对应系数矩阵存在误差的问题,提出了一种基于正则化总体最小二乘的光学线阵遥感影像定位方法。首先依据有理函数模型的定义,构建共线条件方程,利用线性化构建光学线阵影像定位方法和系统误差改正方法,然后依据EIV模型的定义和性质构建相应的优化目标函数,并引入正则化项,依据Lagrange条件极值原理推导基于正则化总体最小二乘的系统误差参数迭代估计方法。实验结果表明:与经典的最小二乘平差算法相比,该方法的总体定位精度提高了11.61%,且比Tikhonov正则化法的定位精度平均提高了6.06%。本文提出方法在不增加任何额外控制信息的情况下,是提高光学线阵影像定位精度的有效途径。
In geometric positioning of optical line array remote sensing image
as it exists error on system error correction parameters corresponding coefficient matrix
a geo-positioning method of remote sensing image of optical line array based on regularized total least squares was proposed in this paper. Firstly
the collinear equation was constructed based on the definition of rational function model
Secondly
the geo-positioning and systematic error correction methods were derived by linearization. Then
the corresponding optimal objective function was constructed based on the definition of the EIV model with a regularization term introduced. The iterative solution method of system error parameters based on regularized total least squares solver was deduced by the Lagrange conditional extremum. Experiment results indicate that
the geo-positioning accuracy of this method is increased by 11.61% compared with the classical least squares adjustment algorithm
and it is increased by 6.06% in contrast to Tikhonov regularization geo-positioning accuracy. The proposed method in this paper can increase the geo-positioning accuracy of linear array CCD images effectively without any extra information.
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