摘要
为满足点衍射干涉测量对解包算法高精度、高效以及抗干扰的检测需求。提出一种基于空洞空间卷积的相移点衍射干涉图像的相位解包方法,通过将自编码器结构和空洞空间卷积结合获得更高的相位解包精度,实现对包裹相位图像可控的多尺度特征提取。根据点衍射图像特点制作的大量多样化数据集对其进行训练和优化,从而实现准确识别包裹相位所在阶次,最终可以快速处理包裹图像得到高精度的解包结果。利用所提方法对实际点衍射干涉图像进行处理,并与ESDI专业干涉图像处理软件以及其他解包算法处理结果进行比对,结果表明:本文解包结果与软件枝切法解包处理结果均方根误差值为0.0222 rad,面形拟合结果与软件面形拟合结果峰谷差值仅为0.0121λ、均方根差值仅为0.0042λ;时间效率上,完成一幅图像的处理平均仅需0.035 s,而传统方法均大于1 s。与其他方法相比,所提方法在处理包裹相位方面具有快速、高精度的特性,为点衍射干涉图像处理的高精度相位解包提供了新的可行方案。
In order to meet the high-precision,high-efficiency,and anti-interference detection requirements of point diffraction interference measurement for phase unwrapping algorithms.Atrous Spatial Convolutional Networks-based phase unwrapping method for phase-shifted point diffraction interference images was proposed.By combining the autoencoder structure and the adaptive spatial convolution,higher phase unwrapping accuracy was achieved,and the degradation of the network model was effectively prevented,realizing controllable multi-scale feature extraction of the wrapped phase image.A large and diverse dataset of point diffraction phase data was used for training and optimization,which accurately identifies the order of the wrapped phase and quickly processed the wrapped image to obtain high-precision unwrapping results.The proposed method was applied to actual point diffraction interference images and compared with results from ESDI professional interference image processing software and other unwrapping algorithms.The results show that the unwrapping results have an RMSE value of 0.0222 rad compared to the software processing results,with a surface fitting result PV difference of only 0.0121λand an RMS difference of only 0.0042λ.In terms of time efficiency,it takes only 0.035 s on average to complete the processing of an image,while the traditional methods are all greater than 1 s.Compared to other methods,the proposed method exhibits fast and high-precision characteristics in unwrapping wrapped phase,providing a new feasible solution for high-precision phase unwrapping in point diffraction interference image processing.
作者
王同盟
高芬
李兵
WANG Tongmeng;GAO Fen;LI Bing(College of Optoelectronic Engineering,Xi'an Technological University,Xi'an 710032,China;State Key Laboratory for Manufacturing Systems Engineering,Xi'an Jiaotong University,Xi'an 710049,China)
出处
《光学精密工程》
EI
CAS
CSCD
北大核心
2024年第2期208-220,共13页
Optics and Precision Engineering
基金
国家自然科学基金资助项目(No.52005383)。
关键词
干涉测量
面形检测
干涉成像
神经网络
相位解包
interferometry
surface measurement
interference fringe
neural networks
phase unwrapping
