Incremental Method for Strain Estimation in Phase‑Contrast OCE Based on Bayesian Neural Network

Rui Mo; Bo Dong; Shengli Xie; Yulei Bai

doi:10.3788/AOS250675

Acta Optica Sinica, Volume. 45, Issue 15, 1511003(2025)

Incremental Method for Strain Estimation in Phase‑Contrast OCE Based on Bayesian Neural Network

Rui Mo¹, Bo Dong^1,2, Shengli Xie¹, and Yulei Bai^1,2、*

Author Affiliations

¹School of Automation, Guangdong University of Technology, Guangzhou 510006, Guangdong , China

²Key Laboratory of Intelligent Detection & Manufacturing Internet of Things, Ministy of Education, Guangdong University of Technology, Guangzhou 510006, Guangdong , China

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Fig. 1. Adaptive incremental method of strain estimation based on Bayesian neural network

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Fig. 2. Network structure for the Bayesian neural network based on strain estimation

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Fig. 3. Experimental results of compression loading. (a) Wrapped phase; (b) strain results from the vector method; (c) strain results from adaptive incremental method based on noise threshold; (d) strain results from the Bayesian neural network; (e) strain results from adaptive incremental method based on Bayesian neural network

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Fig. 4. Comparison of the signal-to-noise ratio of the strain results between the two methods. (a) Signal-to-noise ratio of the strain results of the two methods for the compression loading experiment; (b) signal-to-noise ratio of the strain results of the two methods for the droplet solidification experiment

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Fig. 5. Experimental results of curing. (a) Wrapped phase; (b) strain results from the vector method; (c) strain reults from the adaptive incremental method based on the noise threshold; (d) strain results from the Bayesian neual network; (e) strain results from the adaptive incremental method based on Bayesian neural network

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Table 1. Pseudocode of incremental method

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Table 1. Pseudocode of incremental method

Algorithm 1： algorithm flow of cumulative strain estimation

Input： wrapped phase $ϕ_{s}$ evaluated from ${\tilde{I}}_{s}$ ， $1 \leq s \leq S$ ； preset threshold value $α$

Output： cumulative strain E

01 initial frame $s = 1$ ， interframe interval $Δ s = 1$ and cumulative strain E=0；

02 while $s < S$ do

03 if $s + Δ s > S$ then

04 $Δ s = S - s$

05 end if

06 strain $ε$ ， uncertainty $U$ =BNN $〈A r g \{e x p [i \cdot (ϕ_{s + Δ s} - ϕ_{s})]\}〉$

07 while $U < α$ and $s + Δ s < S$ do

08 $Δ s = Δ s + 1$

09 strain $ε$ ， uncertainty $U$ =BNN $〈A r g \{e x p [i \cdot (ϕ_{s + Δ s} - ϕ_{s})]\}〉$

10 end while

11 while $U > α$ and $Δ s > 1$ do

12 $Δ s = Δ s - 1$

13 strain $ε$ ， uncertainty $U$ =BNN $〈A r g \{e x p [i \cdot (ϕ_{s + Δ s} - ϕ_{s})]\}〉$

14 end while

15 $E = E + ε$

16 $s = s + Δ s$

17 end while

18 returnE

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Rui Mo, Bo Dong, Shengli Xie, Yulei Bai. Incremental Method for Strain Estimation in Phase‑Contrast OCE Based on Bayesian Neural Network[J]. Acta Optica Sinica, 2025, 45(15): 1511003

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Paper Information

Category: Imaging Systems

Received: Feb. 28, 2025

Accepted: May. 7, 2025

Published Online: Aug. 15, 2025

The Author Email: Yulei Bai (ylbai@gdut.edu.cn)

DOI:10.3788/AOS250675

CSTR:32393.14.AOS250675

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology