Generalized Image Acquisition and Analysis

Computational Plenoptic Imaging

The plenoptic function is a ray-based model for light that includes the color spectrum as well as spatial, temporal, and directional variation. Although digital light sensors have greatly evolved in the last years, one fundamental limitation remains: all standard CCD and CMOS sensors integrate over the dimensions of the plenoptic function as they convert photons into electrons; in the process, all visual information is irreversibly lost, except for a two-dimensional, spatially-varying subset - the common photograph. In this state of the art report, we review approaches that optically encode the dimensions of the plenpotic function transcending those captured by traditional photography and reconstruct the recorded information computationally.

Projects

An evaluation of optical flow algorithms for background oriented schlieren imaging

Bradley Atcheson, Wolfgang Heidrich, Ivo Ihrke
In: Experiments in Fluids 2009.



Abstract

The background oriented schlieren method (BOS) allows for accurate flow measurements with a simple experimental configuration. To estimate per-pixel displacement vectors between two images, BOS systems traditionally borrow window-based algorithms from particle image velocimetry. In this paper, we evaluate the performance of more recent optical flow methods in BOS settings. We also analyze the impact of different background patterns, suggesting the use of a pattern with detail at many scales. Experiments with both synthetic and real datasets show that the performance of BOS systems can be significantly improved through a combination of optical flow algorithms and multiscale background.
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Bibtex

@ARTICLE{Atcheson:EiF:2008,
author = {Bradley Atcheson and Wolfgang Heidrich and Ivo Ihrke},
title = {An evaluation of optical flow algorithms for background oriented schlieren imaging},
journal = {Experiments in Fluids},
year = {2008},
volume = {to appear},
number = {},
pages = {},
doi = {10.1007/s00348-008-0572-7}
}
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