Exposure optimization for multi-bit quanta image sensor with ultra-small well capacity

Ka Wai Cheung; Hiu Tung Wong; Derek Ho

doi:10.1109/EDSSC.2016.7785235

Exposure optimization for multi-bit quanta image sensor with ultra-small well capacity

Ka Wai Cheung, Hiu Tung Wong, Derek Ho^*

^*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

1 Citation (Scopus)

Abstract

The effect of ultra-small well capacity is serverely impacting the performance of image sensors fabricated in advanced complementary metal-oxide-semiconductor (CMOS) technologies. Therefore, a new sensing paradigm is required to effectively design pixels at the nanometer scale. In this paper, we present a noise and quantization model for the multi-bit quanta image sensor (Mb-QIS). Using the model to analyze the Mb-QIS, we found that an optimal exposure exists that can minimize the error in photon counting. This result is useful for the design and operation of Mb-QIS based image acquisition systems.

Original language	English
Title of host publication	2016 IEEE International Conference on Electron Devices and Solid-State Circuits, EDSSC 2016
Publisher	IEEE
Pages	165-168
ISBN (Print)	9781509018307
DOIs	https://doi.org/10.1109/EDSSC.2016.7785235
Publication status	Published - 15 Dec 2016
Event	2016 IEEE International Conference on Electron Devices and Solid-State Circuits, EDSSC 2016 - Hong Kong, Hong Kong Duration: 3 Aug 2016 → 5 Aug 2016

Conference

Conference	2016 IEEE International Conference on Electron Devices and Solid-State Circuits, EDSSC 2016
Country/Territory	Hong Kong
City	Hong Kong
Period	3/08/16 → 5/08/16

Funding

This work was funded by the Research Grants Council, grant no.11213515.

Research Keywords

finite well capacity
giga pixel camera
photon counting
quanta image sensor

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10.1109/EDSSC.2016.7785235

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@inproceedings{d9f233c7ec3a4f6f977afea4605f34fa,

title = "Exposure optimization for multi-bit quanta image sensor with ultra-small well capacity",

abstract = "The effect of ultra-small well capacity is serverely impacting the performance of image sensors fabricated in advanced complementary metal-oxide-semiconductor (CMOS) technologies. Therefore, a new sensing paradigm is required to effectively design pixels at the nanometer scale. In this paper, we present a noise and quantization model for the multi-bit quanta image sensor (Mb-QIS). Using the model to analyze the Mb-QIS, we found that an optimal exposure exists that can minimize the error in photon counting. This result is useful for the design and operation of Mb-QIS based image acquisition systems.",

keywords = "finite well capacity, giga pixel camera, photon counting, quanta image sensor",

author = "Cheung, {Ka Wai} and Wong, {Hiu Tung} and Derek Ho",

year = "2016",

month = dec,

day = "15",

doi = "10.1109/EDSSC.2016.7785235",

language = "English",

isbn = "9781509018307",

pages = "165--168",

booktitle = "2016 IEEE International Conference on Electron Devices and Solid-State Circuits, EDSSC 2016",

publisher = "IEEE",

address = "United States",

note = "2016 IEEE International Conference on Electron Devices and Solid-State Circuits, EDSSC 2016 ; Conference date: 03-08-2016 Through 05-08-2016",

}

Cheung, KW, Wong, HT & Ho, D 2016, Exposure optimization for multi-bit quanta image sensor with ultra-small well capacity. in 2016 IEEE International Conference on Electron Devices and Solid-State Circuits, EDSSC 2016., 7785235, IEEE, pp. 165-168, 2016 IEEE International Conference on Electron Devices and Solid-State Circuits, EDSSC 2016, Hong Kong, Hong Kong, 3/08/16. https://doi.org/10.1109/EDSSC.2016.7785235

Exposure optimization for multi-bit quanta image sensor with ultra-small well capacity. / Cheung, Ka Wai; Wong, Hiu Tung ; Ho, Derek.
2016 IEEE International Conference on Electron Devices and Solid-State Circuits, EDSSC 2016. IEEE, 2016. p. 165-168 7785235.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Exposure optimization for multi-bit quanta image sensor with ultra-small well capacity

AU - Cheung, Ka Wai

AU - Wong, Hiu Tung

AU - Ho, Derek

PY - 2016/12/15

Y1 - 2016/12/15

N2 - The effect of ultra-small well capacity is serverely impacting the performance of image sensors fabricated in advanced complementary metal-oxide-semiconductor (CMOS) technologies. Therefore, a new sensing paradigm is required to effectively design pixels at the nanometer scale. In this paper, we present a noise and quantization model for the multi-bit quanta image sensor (Mb-QIS). Using the model to analyze the Mb-QIS, we found that an optimal exposure exists that can minimize the error in photon counting. This result is useful for the design and operation of Mb-QIS based image acquisition systems.

AB - The effect of ultra-small well capacity is serverely impacting the performance of image sensors fabricated in advanced complementary metal-oxide-semiconductor (CMOS) technologies. Therefore, a new sensing paradigm is required to effectively design pixels at the nanometer scale. In this paper, we present a noise and quantization model for the multi-bit quanta image sensor (Mb-QIS). Using the model to analyze the Mb-QIS, we found that an optimal exposure exists that can minimize the error in photon counting. This result is useful for the design and operation of Mb-QIS based image acquisition systems.

KW - finite well capacity

KW - giga pixel camera

KW - photon counting

KW - quanta image sensor

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DO - 10.1109/EDSSC.2016.7785235

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781509018307

SP - 165

EP - 168

BT - 2016 IEEE International Conference on Electron Devices and Solid-State Circuits, EDSSC 2016

PB - IEEE

T2 - 2016 IEEE International Conference on Electron Devices and Solid-State Circuits, EDSSC 2016

Y2 - 3 August 2016 through 5 August 2016

ER -

Exposure optimization for multi-bit quanta image sensor with ultra-small well capacity

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