Analysis and Optimization of Aperture Design in Computational Imaging
Name
1712.04541.pdf
Description
Submitted version
Size
854.62 KB
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Unknown
Checksum (MD5)
b58a677a5dcbaf1d188c5b2fe473eee3
Author(s)
Yedidia, Adam B.
Thrampoulidis, Christos
Wornell, Gregory W.
Date Issued
April 2018
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Yedidia, Adam, Thrampoulidis, Christos and Wornell, Gregory. 2018. "Analysis and Optimization of Aperture Design in Computational Imaging."
Version
Original manuscript
Abstract
© 2018 IEEE. There is growing interest in the use of coded aperture imaging systems for a variety of applications. Using an analysis framework based on mutual information, we examine the fundamental limits of such systems-and the associated optimum aperture coding-under simple but meaningful propagation and sensor models. Among other results, we show that when SNR is high and thermal noise dominates shot noise, spectrally-flat masks, which have 50% transmissivity, are optimal, but that when shot noise dominates thermal noise, randomly generated masks with lower transmissivity offer greater performance. We also provide comparisons to classical pinhole and lens-based cameras.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/icassp.2018.8462521
