Review Of Quanta Image Sensors For Ultralowlight Imaging

• doi: 10.1109/TED.2022.3166716
• title: Review of Quanta Image Sensors for Ultralow-Light Imaging
• publisher: IEEE
• isbn:
• issn: 1557-9646
• rank: 3471
• access_type: CCBY - IEEE is not the copyright holder of this material. Please follow the instructions via https://creativecommons.org/licenses/by/4.0/ to obtain full-text articles and stipulations in the API documentation.
• content_type: Journals
• abstract: The quanta image sensor (QIS) is a photon-counting image sensor that has been implemented using different electron devices, including impact ionization-gain devices, such as the single-photon avalanche detectors (SPADs), and low-capacitance, high conversion-gain devices, such as modified CMOS image sensors (CIS) with deep subelectron read noise and/or low noise readout signal chains. This article primarily focuses on CIS QIS, but recent progress of both types is addressed. Signal processing progress, such as denoising, critical to improving apparent signal-to-noise ratio, is also reviewed as an enabling coinnovation.
• article_number: 9768129
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9768129
• html_url: https://ieeexplore.ieee.org/document/9768129/
• abstract_url: https://ieeexplore.ieee.org/document/9768129/
• publication_title: IEEE Transactions on Electron Devices
• conference_location:
• conference_dates:
• publication_number: 16
• is_number: 9780469
• publication_year: 2022
• publication_date: June 2022
• start_page: 2824
• end_page: 2839
• citing_paper_count: 26
• citing_patent_count: 0
• download_count: 8274
• insert_date: 20220504
• index_terms:
  • ieee_terms:
    • Photonics
    • Single-photon avalanche diodes
    • Sensors
    • Imaging
    • Signal to noise ratio
    • Detectors
    • Performance evaluation
  • author_terms:
    • CMOS image sensor (CIS)
    • denoising
    • image quality
    • low-light sensor
    • photon-counting image sensor
    • quanta image sensor (QIS)
    • subelectron read noise
  • dynamic_index_terms:
    • Image Sensor
    • Camera Sensor
    • Quanta Image Sensor
    • Signal Processing
    • Denoising
    • Noise Reduction
    • Low Noise
    • High Voltage
    • Higher Tendency
    • Photoelectron
    • Photoelectric
    • Deep Neural Network
    • Image Reconstruction
    • Iterative Reconstruction
    • Tomographic Reconstruction
    • Frame Rate
    • Forward Model
    • Thermal Noise
    • Current Noise
    • Bit Error Rate
    • Bit-error-rate
    • Bit Error Ratio
    • Negative Voltage
    • Posterior Mode
    • Map Estimation
    • Maximum A Posteriori Estimate
    • Dark Current
    • Image Reconstruction Algorithm
    • Voltage Noise
    • Incomplete Gamma Function
    • Pixel Pitch
    • Input-referred Noise
    • Reconstruction Module
    • Temporal Noise
    • Low-light Image
    • Polytechnique
    • École Polytechnique
    • Ecole Polytechnique
    • Random Variables
    • Deep Learning
    • Density Data
    • Storage Density
    • Image Processing
    • High Gain
• authors:
  • Author Name: Jiaju Ma
    Affiliation: Gigajot Technology Inc., Pasadena, CA, USA
    Author URL: https://ieeexplore.ieee.org/author/37085509302
    ID: 37085509302
    Order: 1
    Author Affiliations:
    • Gigajot Technology Inc., Pasadena, CA, USA
  • Author Name: Stanley Chan
    Affiliation: School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA
    Author URL: https://ieeexplore.ieee.org/author/37600910000
    ID: 37600910000
    Order: 2
    Author Affiliations:
    • School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA
  • Author Name: Eric R. Fossum
    Affiliation: Thayer School of Engineering, Dartmouth College, Hanover, NH, USA
    Author URL: https://ieeexplore.ieee.org/author/37326789400
    ID: 37326789400
    Order: 3
    Author Affiliations:
    • Thayer School of Engineering, Dartmouth College, Hanover, NH, USA

Image Sensor

• sensor_type: CMOS Image Sensor
• resolution: 16.7 Mpix
• dynamic_range: 100 dB
• pixel_size: 1.1 μm
• dark_current: 0.2 e-/s

Optical Data

• focal_length: not specified
• aperture: not specified
• field_of_view: not specified
• distortion: not specified

Performance Metrics

• frame_rate: 1000 fps
• sensitivity: low-light capability
• power_consumption: 17.6 mW
• noise: 0.19 e-rms

Applications & Benefits

• cell_imaging: enhanced sensitivity in low-light conditions for applications such as medical imaging and security
• benefits: ultra-low light performance, high dynamic range, small pixel size for compact designs

Supporting Organizations

• supported_by: National Science Foundation, Google, Intel, Jet Propulsion Laboratory, NASA

Manuscript Details

• publication_date: June 2022

Relevancy Score

• score: 9
• missing_fields:
  • focal_length
  • aperture
  • field_of_view
  • distortion

Processed JSON Filename

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