ArticleSensors (Basel, Switzerland)2022
Revisiting the Modeling of the Conversion Gain of CMOS Image Sensors with a New Stochastic Approach.
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.
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5 citing papers in PubMed.
- Versatile Electrochemiluminescence Imaging Platform for Multiplexed Biosensing and Point-of-Care Application.Chemical & biomedical imaging · 2026Article
- Article
- The Effect of Pixel Design and Operation Conditions on Linear Output Range of 4T CMOS Image Sensors.Sensors (Basel, Switzerland) · 2024Article
- Modeling Signal-to-Noise Ratio of CMOS Image Sensors with a Stochastic Approach under Non-Stationary Conditions.Sensors (Basel, Switzerland) · 2023Article
- A Novel Method for Developing Thin Resin Scintillator Screens and Application in an X-ray CMOS Imaging Sensor.Sensors (Basel, Switzerland) · 2023Article
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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).
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