Numerical Study of Turbid Slab Optical Properties Reconstruction from Multiple Scattering Signals Using Time-Based Markov Chain Model

The reconstruction of optical properties for opaque mediums is highly desired for medical, atmosphere and aerosol applications. However, the modeling and reconstruction process is highly related with multiple scattering phenomena, which elevates both the complexity and computational costs for such e...

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Bibliographic Details
Published in:Applied sciences 2021-01, Vol.11 (2), p.588
Main Authors: Pan, Hujie, Xu, Qinglin, Li, Xuesong, Wang, Shangning, Xu, Min
Format: Article
Language:English
Subjects:
Backscattering
Computer applications
Markov analysis
Markov chain
Markov chains
Mathematical models
Model accuracy
Monte Carlo simulation
Multiple scatter
multiple scattering
Optical properties
optical properties reconstruction
Optimization algorithms
Photons
Probability
Propagation
Reconstruction
time-based method
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Summary:The reconstruction of optical properties for opaque mediums is highly desired for medical, atmosphere and aerosol applications. However, the modeling and reconstruction process is highly related with multiple scattering phenomena, which elevates both the complexity and computational costs for such efforts. This work introduces a time-based Markov chain method, which uses a sparse transition matrix to represent the likelihood for a photon to transit in the turbid media. The accuracy of the time-based Markov chain model was verified against the forwarding calculations of the scattering-based Markov chain model and Monte Carlo simulations. Then, reconstruction was performed with backscattered photon angular distributions. Based on the characteristics of the sparse transition matrix, the optical properties (droplet diameters) could be obtained layer by layer with transmitted photon distributions at different time durations. It is shown that the time-based Markov chain model can reconstruct the optical properties of a turbid slab with satisfactory accuracy and lower computational costs.
ISSN:2076-3417
2076-3417
DOI:10.3390/app11020588