In-situ multi-scattering tomography

TL;DR

This paper introduces an in-situ multi-scattering tomography method that models arbitrary scattering orders using a parallelizable Monte Carlo approach, enabling large-scale 3D volumetric reconstructions in scattering media.

Contribution

It presents a novel, highly parallelizable Monte Carlo-based tomography model that accounts for multiple scattering in in-situ environments, improving 3D reconstruction accuracy.

Findings

Handles arbitrary scattering orders effectively.

Enables large-scale volumetric scene recovery.

Addresses stability issues in radiative transfer modeling.

Abstract

To recover the three dimensional (3D) volumetric distribution of matter in an object, images of the object are captured from multiple directions and locations. Using these images tomographic computations extract the distribution. In highly scattering media and constrained, natural irradiance, tomography must explicitly account for off-axis scattering. Furthermore, the tomographic model and recovery must function when imaging is done in-situ, as occurs in medical imaging and ground-based atmospheric sensing. We formulate tomography that handles arbitrary orders of scattering, using a monte-carlo model. Moreover, the model is highly parallelizable in our formulation. This enables large scale rendering and recovery of volumetric scenes having a large number of variables. We solve stability and conditioning problems that stem from radiative transfer (RT) modeling in-situ.