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Showing papers by "Anat Levin published in 2015"


Journal ArticleDOI
27 Jul 2015
TL;DR: A computational imaging system that uses interferometry to produce decompositions of light transport in small scenes or volumes, inspired by the optical coherence tomography (OCT) framework, is presented.
Abstract: We present a computational imaging system, inspired by the optical coherence tomography (OCT) framework, that uses interferometry to produce decompositions of light transport in small scenes or volumes. The system decomposes transport according to various attributes of the paths that photons travel through the scene, including where on the source the paths originate, their pathlengths from source to camera through the scene, their wavelength, and their polarization. Since it uses interference, the system can achieve high pathlength resolutions, with the ability to distinguish paths whose lengths differ by as little as ten microns. We describe how to construct and optimize an optical assembly for this technique, and we build a prototype to measure and visualize three-dimensional shape, direct and indirect reflection components, and properties of scattering, refractive/dispersive, and birefringent materials.

61 citations


Posted Content
TL;DR: This work formulation of tomography that handles arbitrary orders of scattering, using a monte-carlo model, enables large scale rendering and recovery of volumetric scenes having a large number of variables and solves stability and conditioning problems that stem from radiative transfer modeling in-situ.
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 o-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.

2 citations