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A comparative study of methods to estimate conversion gain in sub-electron and multi-electron read noise regimes

Authors :
Hendrickson, Aaron
Haefner, David P.
Publication Year :
2023

Abstract

Of all sensor performance parameters, the conversion gain is arguably the most fundamental as it describes the conversion of photoelectrons at the sensor input into digital numbers at the output. Due in part to the emergence of deep sub-electron read noise image sensors in recent years, the literature has seen a resurgence of papers detailing methods for estimating conversion gain in both the sub-electron and multi-electron read noise regimes. Each of the proposed methods work from identical noise models but nevertheless yield diverse procedures for estimating conversion gain. Here, an overview of the proposed methods is provided along with an investigation into their assumptions, uncertainty, and measurement requirements. A sensitivity analysis is conducted using synthetic data for a variety of different sensor configurations. Specifically, the dependence of the conversion gain estimate uncertainty on the magnitude of read noise and quanta exposure is explored. Guidance into the trade-offs between the different methods is provided so that experimenters understand which method is optimal for their application. In support of the reproducible research effort, the MATLAB functions associated with this work can be found on the Mathworks file exchange.<br />Comment: 14 pages, 7 figures, SPIE DCS 2023

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2304.14164
Document Type :
Working Paper
Full Text :
https://doi.org/10.1117/12.2663357