Abstract

A framework with a combination of the radial basis functions (RBFs) method and the least-squares integration method is proposed to improve the integration process from gradient to shape. The principle of the framework is described, and the performance of the proposed method is investigated by simulation. Improvement in accuracy is verified by comparing the result with the usual RBFs-based subset-by-subset stitching method. The proposed method is accurate, automatic, easily implemented, and robust and even works with incomplete data.

© 2013 Optical Society of America

Improvement of high-order least-squares integration method for stereo deflectometry

Hongyu Ren, Feng Gao, and Xiangqian Jiang
Appl. Opt. 54(34) 10249-10255 (2015)

Improvement of least-squares integration method with iterative compensations in fringe reflectometry

Lei Huang and Anand Asundi
Appl. Opt. 51(31) 7459-7465 (2012)

Least-squares method for data reconstruction from gradient data in deflectometry

Hongyu Ren, Feng Gao, and Xiangqian Jiang
Appl. Opt. 55(22) 6052-6059 (2016)

Displacement field analysis based on the combination digital speckle correlation method with radial basis function interpolation

Chen Tang, Linlin Wang, Si Yan, Jian Wu, Liyan Cheng, and Cancan Li
Appl. Opt. 49(24) 4545-4553 (2010)

Optimization method using nodal aberration theory for coaxial imaging systems with radial basis functions based on surface slope

Shuai Zhang, Liuchang Xiao, Xing Zhao, Lipei Song, Yongji Liu, Lingjie Wang, Guangwei Shi, and Weiwei Liu
Appl. Opt. 60(9) 2722-2730 (2021)