Analysis and Optimization of Aperture Design in Computational Imaging

© 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 propaga...

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Bibliographic Details
Main Authors: Yedidia, Adam, Thrampoulidis, Christos, Wornell, Gregory
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2021
Online Access:https://hdl.handle.net/1721.1/137737
Description
Summary:© 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.