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Open Access Correlated Multiple Sampling impact analysis on 1/fE noise for image sensors

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Correlated Multiple Sampling (CMS), which is an extension of Correlated Double Sampling (CDS), is a very popular noise reduction technique used in the readout chain of image sensors. It has been analyzed in the literature, showing that, with an increasingly number M of samples, the total noise tends to a limit value dominated by the pixel 1/f noise. Nevertheless, this approach fails to explain why, in some cases, the total noise measurement may reach a minimum before, against all odds, finally growing with M. This paper shows that an explanation can be found if the pixel noise Power Spectral Density (PSD) varies in 1/fE with a frequency exponent E > 1 instead of E=1.
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Keywords: 1/f noise; Correlated Double Sampling; Correlated Multiple Sampling; Image sensor; pixel

Document Type: Research Article

Publication date: January 13, 2019

This article was made available online on January 13, 2019 as a Fast Track article with title: "Correlated Multiple Sampling impact analysis on 1/fᴱ noise for image sensors".

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  • For more than 30 years, the Electronic Imaging Symposium has been serving those in the broad community - from academia and industry - who work on imaging science and digital technologies. The breadth of the Symposium covers the entire imaging science ecosystem, from capture (sensors, camera) through image processing (image quality, color and appearance) to how we and our surrogate machines see and interpret images. Applications covered include augmented reality, autonomous vehicles, machine vision, data analysis, digital and mobile photography, security, virtual reality, and human vision. IS&T began sole sponsorship of the meeting in 2016. All papers presented at EIs 20+ conferences are open access.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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