Abstract

This study proposes a modified sub-aperture stitching algorithm, which uses an image sharpening algorithm and particle swarm optimization to improve the stitching accuracy. In sub-aperture stitching interferometers with high positional accuracy, the high-frequency components of measurements are more important than the low-frequency components when compensating for position errors using a sub-aperture stitching algorithm. Thus we use image sharpening algorithms to strengthen the high-frequency components of measurements. When using image sharpening algorithms, sub-aperture stitching algorithms based on the least-squares method easily become trapped at locally optimal solutions. However, particle swarm optimization is less likely to become trapped at a locally optimal solution, thus we utilized this method to develop a more robust algorithm. The results of simulations showed that our algorithm compensated for position errors more effectively than the existing algorithm. An experimental comparison with full aperture-testing results demonstrated the validity of the new algorithm.

© 2014 Optical Society of Korea

Spectral reflectance reconstruction based on wideband multi-illuminant imaging and a modified particle swarm optimization algorithm

Xinmeng Zhang, Guihua Cui, Xiukai Ruan, Di Cui, Xiaohong Gao, Qifan Chen, Yuan Yao, Manuel Melgosa, and Suchitra Sueeprasan
Opt. Express 32(3) 2942-2958 (2024)

Pump scheme for gain-flattened Raman fiber amplifiers using improved particle swarm optimization and modified shooting algorithm

Hai-ming Jiang, Kang Xie, and Ya-fei Wang
Opt. Express 18(11) 11033-11045 (2010)

Hybrid particle swarm global optimization algorithm for phase diversity phase retrieval

P. G. Zhang, C. L. Yang, Z. H. Xu, Z. L. Cao, Q. Q. Mu, and L. Xuan
Opt. Express 24(22) 25704-25717 (2016)

Sub-aperture stitching interferometry using stereovision positioning technique

Pengfei Zhang, Hong Zhao, Xiang Zhou, and Jinjun Li
Opt. Express 18(14) 15216-15222 (2010)

Phase diversity method based on an improved particle swarm algorithm used in co-phasing error detection

Yingjian Ge, Shengqian Wang, and Hao Xian
Appl. Opt. 59(31) 9735-9743 (2020)