A ground control points sampling design method based on smallest singular value

Pu Wang; Wei An; Xing Pu Deng; Jing Guo; Jun Li

doi:10.1117/12.2065796

15 October 2014 A ground control points sampling design method based on smallest singular value

Pu Wang, Wei An, Xing Pu Deng, Jing Guo, Jun Li

Proceedings Volume 9244, Image and Signal Processing for Remote Sensing XX; 92441E (2014) https://doi.org/10.1117/12.2065796
Event: SPIE Remote Sensing, 2014, Amsterdam, Netherlands

Abstract

The Ground Control Points (GCPs) are widely used in geometric correction for remote sensing imagery, and the distribution of them is a key factor which affects the accuracy and quality of image correction. In this paper, we propose a new sampling design method, called Smallest Singular Value-based Sampling (SSVS), to obtain the optimal distribution of the GCPs. When the geometric correction of remote sensing imagery is performed with a 2D or 3D polynomial function model, the estimation of geometric correction model parameters can be interpreted as an estimation of regression coefficients with a Multiple Linear Regression(MLR) model, whose design matrix depends on the coordinates of GCPs. From the perspective of regression model, the design matrix of MLR should be optimized to obtain the most accurate regression coefficients. In this paper, it has been proved that the Smallest Singular Value(SSV) of design matrix is inversely proportional to the upper bound of estimation errors. By choosing the optimal distribution of GCPs, the SSV of design matrix can be maximized and the upper bound of estimation errors can be minimized. Therefore, the SSV of design matrix is used as a criterion, and the objective of SSVS is to find the sample pattern that has the biggest SSV. In this paper, the simulation annealing is employed to search the optimal pattern. Two experiments were carried out to test SSVS. The results indicate that the SSVS is an effective GCPs sampling design method and can be applied to evaluate upper bound of estimation error.

Citation Download Citation

Pu Wang, Wei An, Xing Pu Deng, Jing Guo, and Jun Li "A ground control points sampling design method based on smallest singular value", Proc. SPIE 9244, Image and Signal Processing for Remote Sensing XX, 92441E (15 October 2014); https://doi.org/10.1117/12.2065796

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