Work

Photon Counting Histogram Expectation Maximization Algorithm for Characterization of Deep Sub-Electron Read Noise Sensors

Year: 2023

Type: article

Abstract: We develop a novel algorithm for characterizing Deep Sub-Electron Read Noise (DSERN) image sensors. This algorithm is able to simultaneously compute maximum likelihood estimates of quanta exposure, conversion gain, bias, and read noise of DSERN pixels from a single sample of data with less uncertainty than the traditional photon transfer method. Methods for estimating the starting point of the algorithm are also provided to allow for automated analysis. Demonstration through Monte Carlo numerical experiments are carried out to show the effectiveness of the proposed technique. In support of the reproducible research effort, all of the simulation and analysis tools developed are available on the MathWorks file exchange (Hendrickson and Haefner, 2022).

Source: IEEE Journal of the Electron Devices Society

DOI: 10.1109/jeds.2023.3290106

Authors: Aaron J. Hendrickson, David P. Haefner

Institutions: Naval Air Warfare Center Aircraft Division, United States Navy, United States Army

Language: English

Topic: CCD and CMOS Imaging Sensors

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,350

OpenAlex ID: W4382203107