Cmos Image Sensor Noise Analysis Through Noise Power Spectral Density Including Undersampling Effect Due To Readout Sequence

• doi: 10.1109/TED.2014.2329500
• title: CMOS Image Sensor Noise Analysis Through Noise Power Spectral Density Including Undersampling Effect Due to Readout Sequence
• publisher: IEEE
• isbn:
• issn: 1557-9646
• rank: 1770
• access_type: LOCKED
• content_type: Journals
• abstract: This paper presents a noise analysis in the frequency domain using noise power spectral density and considering the undersampling process coming from the native readout circuit sequence of image sensors. It reveals aliasing effect impacting the noise level of the image sensor. Key parameters of the undersampling process, such as sampling period, power spectral density level, and type, are explored. Low-frequency noise and particularly 1/f noise impact show a major impact in results. The new calculation algorithm is implemented in MATLAB software. Two CMOS image sensor technologies are used to perform a comparison between noise estimation and measurements. This comparison shows a very good correlation between estimations and measurements.
• article_number: 6841629
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6841629
• html_url: https://ieeexplore.ieee.org/document/6841629/
• abstract_url: https://ieeexplore.ieee.org/document/6841629/
• publication_title: IEEE Transactions on Electron Devices
• conference_location:
• conference_dates:
• publication_number: 16
• is_number: 6861490
• publication_year: 2014
• publication_date: Aug. 2014
• start_page: 2834
• end_page: 2842
• citing_paper_count: 8
• citing_patent_count: 0
• download_count: 1570
• insert_date: 20140623
• index_terms:
  • ieee_terms:
    • Noise
    • Mathematical model
    • Image sensors
    • Integrated circuit modeling
    • Silicon compounds
    • Spectral analysis
    • Photodiodes
  • author_terms:
    • Aliasing
    • APS
    • CMOS image sensors (CIS)
    • correlated double sampling (CDS)
    • low-frequency noise (LFN)
    • noise power spectral density
    • thermal noise
    • undersampling.
    • Aliasing
    • APS
    • CMOS image sensors (CIS)
    • correlated double sampling (CDS)
    • low-frequency noise (LFN)
    • noise power spectral density
    • thermal noise
    • undersampling
  • dynamic_index_terms:
    • Power Spectral Density
    • Spectral Function
    • Image Sensor
    • Camera Sensor
    • Noise Analysis
    • Noise Power Spectral Density
    • Readout Sequence
    • Sampling Period
    • Frequency Domain
    • Measurement Noise
    • Noise Estimation
    • Readout Circuit
    • Aliasing Effect
    • Sample Processing
    • Sampling Frequency
    • White Noise
    • Spectral Analysis
    • Output Signal
    • Sample Holder
    • Noise Sources
    • Spectral Domain
    • Output Stage
    • PIN Photodiode
    • Conversion Gain
    • Noise Values
    • Common Circuit
    • Test Vehicle
    • Corner Frequency
    • Command Signal
    • Analog Output
    • Pixel Array
• authors:
  • Author Name: Philippe Martin-Gonthier
    Affiliation: Integrated Image Sensor Laboratory, Université de Toulouse, Toulouse, France
    Author URL: https://ieeexplore.ieee.org/author/38278141700
    ID: 38278141700
    Order: 1
    Author Affiliations:
    • Integrated Image Sensor Laboratory, Université de Toulouse, Toulouse, France
  • Author Name: Pierre Magnan
    Affiliation: Integrated Image Sensor Laboratory, Université de Toulouse, Toulouse, France
    Author URL: https://ieeexplore.ieee.org/author/37400751600
    ID: 37400751600
    Order: 2
    Author Affiliations:
    • Integrated Image Sensor Laboratory, Université de Toulouse, Toulouse, France

Image Sensor

• sensor_type: CMOS
• resolution: 256x256 pixels
• dynamic_range: Not specified
• pixel_size: Not specified
• dark_current: Not specified

Optical Data

• focal_length: Not specified
• aperture: Not specified
• field_of_view: Not specified
• distortion: Not specified

Performance Metrics

• noise: Total input referred noise of 47e- rms for CIS 0.15 μm and 3.4e- rms for CIS 0.18 μm.

Applications & Benefits

• cell_imaging: CMOS image sensors are utilized in commercial and high-end applications such as smartphones, medical devices, and automotive systems.
• benefits: Significant performance enhancements such as dark current, quantum efficiency, and fill factor.

Supporting Organizations

• supported_by: ISAE-CIMI research group

Manuscript Details

• publication_date: Aug. 2014

Relevancy Score

• score: 10
• missing_fields:
  • fill factor
  • quantum efficiency
  • power consumption
  • readout speed
  • noise sources
  • analog-to-digital conversion techniques
  • design considerations

Processed JSON Filename

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