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Markov Chain and Monte Carlo Predictions for Light Multiple Scattering Applications

机译:轻多重散射应用的马尔可夫链和蒙特卡洛预测

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Multiple scattering is considered both an interference source and tentatively the information to measure the optical properties of mediums in many engineering applications, such as fuel spray atomization in IC engines, medical diagnostics for bio-tissues, and atmosphere detection, etc. However, the understanding of multiple scattering is hindered by the stochastic nature of random scattering, especially in the intermediate regime. This work reports a Markov Chain solution to analyze the angular distribution of transmitted photons and compared against a typical method, Monte Carlo algorithm. The Markov Chain method is then utilized to perform an inversion process to derive the optical properties inside the medium and various reconstruction algorithms were tested. Results have shown that Markov Chain method is a viable technique in reducing the computational cost yet preserving the computation fidelity.
机译:在许多工程应用中,多重散射既被视为干扰源,也被暂时视为用于测量介质的光学特性的信息,例如IC引擎中的燃料喷雾雾化,生物组织的医学诊断和大气检测等。随机散射的随机性阻碍了多次散射的发生,特别是在中间状态下。这项工作报告了一个马尔可夫链解决方案,用于分析透射光子的角度分布,并与典型方法蒙特卡洛算法进行了比较。然后,利用马尔可夫链方法执行反演过程以导出介质内部的光学特性,并测试了各种重建算法。结果表明,马尔可夫链法是一种在降低计算成本的同时保持计算保真度的可行技术。

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