Modeling Signal-to-Noise Ratio of CMOS Image Sensors with a Stochastic Approach under Non-Stationary Conditions.
CMOS image sensor
gated imaging
signal-to-noise ratio (SNR)
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
23 Aug 2023
23 Aug 2023
Historique:
received:
27
07
2023
revised:
10
08
2023
accepted:
21
08
2023
medline:
9
9
2023
pubmed:
9
9
2023
entrez:
9
9
2023
Statut:
epublish
Résumé
A stochastic model for characterizing the conversion gain of Active Pixel Complementary metal-oxide-semiconductor (CMOS) image sensors (APS), assuming stationary conditions was recently presented in this journal. In this study, we extend the stochastic approach to non-stationary conditions. Non-stationary conditions occur in gated imaging applications. This new stochastic model, which is based on fundamental physical considerations, enlightens us with new insights into gated CMOS imaging, regardless of the sensor. The Signal-to-Noise Ratio (SNR) is simulated, allowing optimized performance. The conversion gain should be determined under stationary conditions.
Identifiants
pubmed: 37687800
pii: s23177344
doi: 10.3390/s23177344
pmc: PMC10490096
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Smart Imaging Consortium Israel Innovation Authority
ID : 74391
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