15Mu Mathrmm Dual Conversion Gain Backside Illuminated Image Sensor Using Stacked Pixel Level Connections With 13Kefullwell Capacitance And 08Enoise

• doi: 10.1109/IEDM.2018.8614484
• title: $1.5\mu \mathrm{m}$ Dual Conversion Gain, Backside Illuminated Image Sensor Using Stacked Pixel Level Connections with 13ke-Full-Well Capacitance and 0.8e-Noise
• publisher: IEEE
• isbn: 978-1-7281-1988-5
• issn: 0163-1918
• rank: 1
• access_type: LOCKED
• content_type: Conferences
• abstract: A 1.5μm pixel size, 8 mega pixel density, dual conversion gain (DCG), back side illuminated CMOS image sensor (CIS) is described having a linear full-well capacity (FWC) of 13ke- and total noise of 0.8e-RMS at 8x gain. The sensor adopts a world smallest 1.5μm pitch, stacked pixel-level connection (SPLC) technology with greater than 8M connections, maximizing fill-factor of the photodiode and dimensions of the associated transistors to achieve a large FWC and low noise performance at the same time. In addition, by allocating transistors into two different layers, the DCG function can be realized with 1.5μm pixel size.
• article_number: 8614484
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8614484
• html_url: https://ieeexplore.ieee.org/document/8614484/
• abstract_url: https://ieeexplore.ieee.org/document/8614484/
• publication_title: 2018 IEEE International Electron Devices Meeting (IEDM)
• conference_location: San Francisco, CA, USA
• conference_dates: 1-5 Dec. 2018
• publication_number: 8601505
• is_number: 8614478
• publication_year: 2018
• publication_date: 1-5 Dec. 2018
• start_page: 10.1.1
• end_page: 10.1.4
• citing_paper_count: 6
• citing_patent_count: 0
• download_count: 2175
• insert_date: 20190117
• index_terms:
  • ieee_terms:
    • Transistors
    • Image sensors
    • Gain
    • Capacitance
    • Dynamic range
    • Stacking
    • MOS capacitors
  • dynamic_index_terms:
    • Image Sensor
    • Camera Sensor
    • Conversion Gain
    • Dual Conversion Gain
    • Photodiode
    • Low Noise
    • Dynamic Range
    • Internet Of Things
    • Internet-of-Things
    • Low Light
    • High Conversion
    • High Gain
    • Quantum Efficiency
    • Lower Gain
    • High Dynamic Range
    • High-dynamic-range
    • Sensor Layer
    • High Dynamic Range Image
    • Low Crosstalk
• isbn_formats:
  • format: Print on Demand(PoD) ISBN, value: 978-1-7281-1988-5, isbnType: New-2005
  • format: Electronic ISBN, value: 978-1-7281-1987-8, isbnType: New-2005
• authors:
  • Author Name: Vincent C. Venezia
    Affiliation: Omni Vision Technologies, Santa Clara, CA
    Author URL: https://ieeexplore.ieee.org/author/37563921200
    ID: 37563921200
    Order: 1
    Author Affiliations:
    • Omni Vision Technologies, Santa Clara, CA
  • Author Name: Alan Chih-Wei Hsiung
    Affiliation: Omni Vision Technologies, Santa Clara, CA
    Author URL: https://ieeexplore.ieee.org/author/37086595482
    ID: 37086595482
    Order: 2
    Author Affiliations:
    • Omni Vision Technologies, Santa Clara, CA
  • Author Name: Kelvin Ai
    Affiliation: Omni Vision Technologies, Santa Clara, CA
    Author URL: https://ieeexplore.ieee.org/author/37086591715
    ID: 37086591715
    Order: 3
    Author Affiliations:
    • Omni Vision Technologies, Santa Clara, CA
  • Author Name: Xiang Zhao
    Affiliation: Omni Vision Technologies, Santa Clara, CA
    Author URL: https://ieeexplore.ieee.org/author/37086593476
    ID: 37086593476
    Order: 4
    Author Affiliations:
    • Omni Vision Technologies, Santa Clara, CA
  • Author Name: Zhiqiang Lin
    Affiliation: Omni Vision Technologies, Santa Clara, CA
    Author URL: https://ieeexplore.ieee.org/author/37086597130
    ID: 37086597130
    Order: 5
    Author Affiliations:
    • Omni Vision Technologies, Santa Clara, CA
  • Author Name: Duli Mao
    Affiliation: Omni Vision Technologies, Santa Clara, CA
    Author URL: https://ieeexplore.ieee.org/author/37086595622
    ID: 37086595622
    Order: 6
    Author Affiliations:
    • Omni Vision Technologies, Santa Clara, CA
  • Author Name: Armin Yazdani
    Affiliation: Omni Vision Technologies, Santa Clara, CA
    Author URL: https://ieeexplore.ieee.org/author/37086594345
    ID: 37086594345
    Order: 7
    Author Affiliations:
    • Omni Vision Technologies, Santa Clara, CA
  • Author Name: Eric A. G. Webster
    Affiliation: Omni Vision Technologies, Santa Clara, CA
    Author URL: https://ieeexplore.ieee.org/author/37599902600
    ID: 37599902600
    Order: 8
    Author Affiliations:
    • Omni Vision Technologies, Santa Clara, CA
  • Author Name: Lindsay A. Grant
    Affiliation: Omni Vision Technologies, Santa Clara, CA
    Author URL: https://ieeexplore.ieee.org/author/37268638300
    ID: 37268638300
    Order: 9
    Author Affiliations:
    • Omni Vision Technologies, Santa Clara, CA

Image Sensor

• sensor_type: CMOS
• resolution: 8 mega pixels
• dynamic_range: 83.8 dB
• pixel_size: 1.5 µm
• dark_current: N/A

Optical Data

• focal_length: N/A
• aperture: N/A
• field_of_view: N/A
• distortion: N/A

Performance Metrics

• frame_rate: 30 fps
• signal_to_noise_ratio: N/A
• sensitivity: N/A
• shutter_speed: N/A
• power_consumption: N/A
• noise: 0.8 e- RMS

Applications & Benefits

• cell_imaging: Enables high-quality images in low and high light conditions for applications such as smartphones, surveillance, and medical imaging.
• benefits: Achieves good HDR performance and improved low light imaging due to high conversion gain and dynamic range.

Supporting Organizations

• supported_by: OmniVision Technologies, Santa Clara CA

Manuscript Details

• publication_date: 1-5 Dec. 2018

Relevancy Score

• score: 10
• missing_fields:
  • dark_current
  • optical_data.focal_length
  • optical_data.aperture
  • optical_data.field_of_view
  • optical_data.distortion
  • performance_metrics.signal_to_noise_ratio
  • performance_metrics.sensitivity
  • performance_metrics.power_consumption
  • performance_metrics.shutter_speed

Processed JSON Filename

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