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Proceedings Paper

A simulation framework for the design and evaluation of computational cameras
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Paper Abstract

In the emerging field of computational imaging, rapid prototyping of new camera concepts becomes increasingly difficult since the signal processing is intertwined with the physical design of a camera. As novel computational cameras capture information other than the traditional two-dimensional information, ground truth data, which can be used to thoroughly benchmark a new system design, is also hard to acquire. We propose to bridge this gap by using simulation. In this article, we present a raytracing framework tailored for the design and evaluation of computational imaging systems. We show that, depending on the application, the image formation on a sensor and phenomena like image noise have to be simulated accurately in order to achieve meaningful results while other aspects, such as photorealistic scene modeling, can be omitted. Therefore, we focus on accurately simulating the mandatory components of computational cameras, namely apertures, lenses, spectral filters and sensors. Besides the simulation of the imaging process, the framework is capable of generating various ground truth data, which can be used to evaluate and optimize the performance of a particular imaging system. Due to its modularity, it is easy to further extend the framework to the needs of other fields of application. We make the source code of our simulation framework publicly available and encourage other researchers to use it to design and evaluate their own camera designs.1

Paper Details

Date Published: 21 June 2019
PDF: 12 pages
Proc. SPIE 11061, Automated Visual Inspection and Machine Vision III, 1106102 (21 June 2019); doi: 10.1117/12.2527599
Show Author Affiliations
Thomas Nürnberg, Karlsruher Institut für Technologie (Germany)
Maximilian Schambach, Karlsruher Institut für Technologie (Germany)
David Uhlig, Karlsruher Institut für Technologie (Germany)
Michael Heizmann, Karlsruher Institut für Technologie (Germany)
Fernando Puente León, Karlsruher Institut für Technologie (Germany)

Published in SPIE Proceedings Vol. 11061:
Automated Visual Inspection and Machine Vision III
Jürgen Beyerer; Fernando Puente León, Editor(s)

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