Towards computational imaging for intelligence in highly scattering aerosols

摘要

Aerosols like fog reduce situational awareness and cause down-time that for critical systems or operations is unacceptable. Information is lost to the random scattering and absorption of light by tiny particles. Computational diffuse optical imaging methods show promise for interpreting the light transmitted or reflected through fog, enabling sensing and imaging to improve situational awareness. Developing this capability first requires verification and validation of diffuse transport models in fog. For this reason, analytical solutions were developed and compared to experimental data captured at the Sandia National Laboratory Fog Chamber facility. The weak angular dependence and diffusion approximations to the radiative transfer equation were found sufficient to predict light propagation in fog under the appropriate conditions.