Method of multilayer object sectioning based on a light scattering model

IF 1.1 Q4 OPTICS Computer Optics Pub Date : 2023-10-01 DOI:10.18287/2412-6179-co-1266
S.D. Bazhitov, A.V. Larichev, A.V. Razgulin, T.E. Romanenko
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Abstract

We discuss a problem of reconstructing (sectioning) multilayer object images in observed images obtained by focusing the imaging system on each layer and containing spurious blurry images of neighboring layers. The blurring model used describes a physical process of incoherent light scattering in the Fresnel approximation with a priori unknown parameters of the point spread function. We propose a method of "Boundary separation" of sectioning, which combines the use of a physical blur model with modern methods of blur estimating and edge detection. The results of testing the "Boundary separation" method on the data of physical experiments with different-scale model multilayer objects are analyzed and compared with the existing methods for solving the optical sectioning problem. It is concluded that the method is most effective on multilayer objects with clearly defined boundaries, on which the method has demonstrated almost complete restoration of the desired layers.
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基于光散射模型的多层物体分割方法
本文讨论了通过将成像系统聚焦在每一层上并包含相邻层的伪模糊图像而获得的观测图像中重建(分割)多层目标图像的问题。所采用的模糊模型描述了非相干光散射在菲涅耳近似中的物理过程,其中点扩散函数的先验参数未知。我们提出了一种分割的“边界分离”方法,它将物理模糊模型的使用与现代模糊估计和边缘检测方法相结合。对“边界分离”方法在不同尺度模型多层物体物理实验数据上的测试结果进行了分析,并与现有的光学切片方法进行了比较。结果表明,该方法对具有明确边界的多层目标最有效,在这些目标上,该方法几乎完全恢复了期望的图层。
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来源期刊
Computer Optics
Computer Optics OPTICS-
CiteScore
4.20
自引率
10.00%
发文量
73
审稿时长
9 weeks
期刊介绍: The journal is intended for researchers and specialists active in the following research areas: Diffractive Optics; Information Optical Technology; Nanophotonics and Optics of Nanostructures; Image Analysis & Understanding; Information Coding & Security; Earth Remote Sensing Technologies; Hyperspectral Data Analysis; Numerical Methods for Optics and Image Processing; Intelligent Video Analysis. The journal "Computer Optics" has been published since 1987. Published 6 issues per year.
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