In-situ multi-view multi-scattering stochastic tomography

To recover the three dimensional (3D) volumetric matter distribution in an object, the object is imaged from multiple directions and locations. Using these images, tomographic computations seek the distribution. When scattering is significant and under constrained irradiance, tomography must explici...

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Bibliographic Details
Published in2016 IEEE International Conference on Computational Photography (ICCP) pp. 1 - 12
Main Authors Holodovsky, Vadim, Schechner, Yoav Y., Levin, Anat, Levis, Aviad, Aides, Amit
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2016
Subjects
Aerosols
Atmospheric modeling
Cameras
Estimation
Photonics
Scattering
Sun
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Summary:To recover the three dimensional (3D) volumetric matter distribution in an object, the object is imaged from multiple directions and locations. Using these images, tomographic computations seek the distribution. When scattering is significant and under constrained irradiance, tomography must explicitly account for off-axis scattering. Furthermore, tomographic 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. The model is highly parallelizable in our formulation. This can enable 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 modeling in-situ.
DOI:10.1109/ICCPHOT.2016.7492869