A guided Monte Carlo radiative transfer method using mixture importance sampling

School of Mathematical and Physical Sciences, Dalian University of Technology, Panjin, PR China
e-mail: fugiya@dlut.edu.cn

Received: 22 April 2019
Accepted: 15 July 2019

Abstract

In order to investigate the source of uncertainties for the Monte Carlo radiative transfer method, a path space formulation is proposed which expresses the integral form of the radiative transfer equation. It has been determined that some of the uncertainties depend on the sampling of photon propagation directions. To reduce this kind of uncertainty, we propose a guided Monte Carlo (GMC) method based on a direction mixture importance sampling strategy for simulating radiative transfer in a scattering medium. We validated the GMC method by implementing it in a backward Monte Carlo radiative transfer (BMCRT) code for the plane-parallel medium. Similar to the usual BMCRT method, the solution is determined by tracing photons from the detector towards the radiation source in the backward GMC method. Through test examples, we demonstrate the validity of the direction mixture importance sampling strategy and the GMC method.