Evidence map›Paper›PMID 36236717›Full record

ArticleSensors (Basel, Switzerland)2022

Revisiting the Modeling of the Conversion Gain of CMOS Image Sensors with a New Stochastic Approach.

Gil Cherniak, Amikam Nemirovsky, Yael Nemirovsky

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Gil CherniakElectrical Engineering Department, Technion-Israel Institute of Technology, Haifa 3200003, Israel.ORCID 0000-0002-1820-762X
Amikam NemirovskyDepartment of Electrical Engineering, Kinneret College on the Sea of Galilee, Tzemah 1513200, Israel.
Yael NemirovskyElectrical Engineering Department, Technion-Israel Institute of Technology, Haifa 3200003, Israel.

Funding

"Smart Imaging" Consortium Israel Innovation Authority 74391
6 · The paper itself

Abstract

A stochastic model for characterizing the conversion gain of Active Pixel Complementary metal-oxide-semiconductor (CMOS) image sensors (APS) with at least four transistors is presented. This model, based on the fundamental principles of electronic noise, may provide a reliable calibration of the gain conversion, which is one of the most important parameters of CMOS Image Sensor pixels. The new model revisits the "gold standard" ratio method of the measured variance of the shot noise to the mean value. The model assumes that shot noise is the dominant noise source of the pixel. The microscopic random time-dependent voltage of any shot noise electron charging the junction capacitance C of the sensing node may have either an exponential form or a step form. In the former case, a factor of 1/2 appears in the variance to the mean value, namely, q/2C is obtained. In the latter case, the well-established ratio q/C remains, where q is the electron charge. This correction factor affects the parameters that are based on the conversion gain, such as quantum efficiency and noise. The model has been successfully tested for advanced image sensors with six transistors fabricated in a commercial FAB, applying a CMOS 180 nm technology node with four metals. The stochastic modeling is corroborated by measurements of the quantum efficiency and simulations with advanced software (Lumerical).

Indexed as

CMOS Image Sensorconversion gainglobal shutterlow read noisephoton countingpinned photodiodeshot noise

Identifiers

PMID36236717
PMCPMC9570612

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.