@inproceedings{74c4b75cc0e54ccea81da51d46030a9a,
title = "UNet++ for Estimating Physical Parameters from Newton{\textquoteright}s Rings",
abstract = "Newton{\textquoteright}s rings pattern is frequently encountered in optical interferometry, and by extracting the phase contained in it, the measured physical parameter information can be obtained. According to the purpose of point-to-point mapping of the image to be analyzed, a method based on UNet++ to extract the phase of Newton{\textquoteright}s rings is proposed. Once the network training is completed, the continuous phase including the curvature radius and ring{\textquoteright}s center coordinate can be directly predicted from a single Newton{\textquoteright}s rings pattern immediately. The relative error of the curvature radius obtained by parameter fitting the phase is less than 0.83%, and the error of ring{\textquoteright}s center coordinate is close to 0 pixel. In order to further improve the results of curvature radius estimation, the parameter estimation results obtained by UNet++ are taken as the initial value and corrected by the least-squares fitting method. Experimental results show that for the Newton{\textquoteright}s rings pattern containing -5 dB Gaussian noise, the relative error of the corrected curvature radius is no higher than 0.31%.",
keywords = "Newton{\textquoteright}s rings, UNet++, curvature radius, phase",
author = "Saihui Fan and Mingfeng Lu and Xiaoxin Xiong and Jinmin Wu and Deming Shen and Ran Tao",
note = "Publisher Copyright: {\textcopyright} 2023 SPIE. All rights reserved.; 3rd International Conference on Optics and Image Processing, ICOIP 2023 ; Conference date: 14-04-2023 Through 16-04-2023",
year = "2023",
doi = "10.1117/12.2689318",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Bingxiang Li and Chao Ren",
booktitle = "Third International Conference on Optics and Image Processing, ICOIP 2023",
address = "United States",
}