Imaging through scattering media with a learning based prior

Florian Schiffers, Lionel Fiske, Pablo Ruiz, Aggelos K. Katsaggelos, Oliver Cossairt

Research output: Contribution to journalConference articlepeer-review

Abstract

Imaging through scattering media finds applications in diverse fields from biomedicine to autonomous driving. However, interpreting the resulting images is difficult due to blur caused by the scattering of photons within the medium. Transient information, captured with fast temporal sensors, can be used to significantly improve the quality of images acquired in scattering conditions. Photon scattering, within a highly scattering media, is well modeled by the diffusion approximation of the Radiative Transport Equation (RTE). Its solution is easily derived which can be interpreted as a Spatio-Temporal Point Spread Function (ST-PSF). In this paper, we first discuss the properties of the ST-PSF and subsequently use this knowledge to simulate transient imaging through highly scattering media. We then propose a framework to invert the forward model, which assumes Poisson noise, to recover a noise-free, unblurred image by solving an optimization problem.

Original languageEnglish (US)
Article number306
JournalIS and T International Symposium on Electronic Imaging Science and Technology
Volume2020
Issue number6
DOIs
StatePublished - Jan 26 2020
Event2020 Intelligent Robotics and Industrial Applications Using Computer Vision Conference, IRIACV 2020 - Burlingame, United States
Duration: Jan 26 2020Jan 30 2020

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Human-Computer Interaction
  • Software
  • Electrical and Electronic Engineering
  • Atomic and Molecular Physics, and Optics

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