Generalized Image Acquisition and Analysis

On Plenoptic Multiplexing and Reconstruction

Photography has been striving to capture an ever increasing amount of visual information in a single image. Digital sensors, however, are limited to recording a small subset of the desired information at each pixel. A common approach to overcoming the limitations of sensing hardware is the optical multiplexing of high-dimensional data into a photograph. While this is a well-studied topic for imaging with color filter arrays, we develop a mathematical framework that generalizes multiplexed imaging to all dimensions of the plenoptic function. This framework unifies a wide variety of existing approaches to analyze and reconstruct multiplexed data in either the spatial or the frequency domain. We demonstrate many practical applications of our framework including high-quality light field reconstruction, the first comparative noise analysis of light field attenuation masks, and an analysis of aliasing in multiplexing applications.

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Three-Dimensional Kaleidoscopic Imaging

Ivo Ihrke, Ilya Reshetouski, Alkhazur Manakov, Hans-Peter Seidel
Computational Optical Sensing and Imaging (COSI) 2012



Abstract

Planar mirror systems are capable of generating many virtual views, yet their practical use for multi-view imaging has been hindered by limiting configurations that enable view decomposition. In this work we lift those restrictions.
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Bibtex

@inproceedings{Ihrke:12,
author = {Ivo Ihrke and Ilya Reshetouski and Alkhazur Manakov and Hans-Peter Seidel},
booktitle = {Computational Optical Sensing and Imaging},
journal = {Computational Optical Sensing and Imaging},
pages = {CTu4B.8},
publisher = {Optical Society of America},
title = {Three-Dimensional Kaleidoscopic Imaging},
year = {2012},
}
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