A Closedloop Allelectronic Pixelwise Adaptive Imaging System For High Dynamic Range Videography

• doi: 10.1109/TCSI.2020.2973396
• title: A Closed-Loop, All-Electronic Pixel-Wise Adaptive Imaging System for High Dynamic Range Videography
• publisher: IEEE
• isbn:
• issn: 1558-0806
• rank: 664
• access_type: LOCKED
• content_type: Journals
• abstract: Digital cameras expose and readout all pixels in accordance with a global sample clock. This rigid global control of exposure and sampling is problematic for capturing scenes with large variance in brightness and motion, and may cause regions of motion blur, under- and overexposure. To address these issues, we developed a CMOS imaging system that automatically adjusts each pixel’s exposure and sampling rate to fit local motion and brightness. This system consists of an image sensor with pixel-addressable exposure configurability in combination with a real-time, per-pixel exposure controller. It operates in a closed-loop to sample, detect and optimize each pixel’s exposure and sampling rate for optimal acquisition. Per-pixel exposure control is implemented using all-integrated electronics without external optical modulation. This reduces system complexity and power consumption compared to existing solutions. Implemented using standard 130nm CMOS process, the chip has $256\times256$ pixels and consumes 7.31mW. To evaluate performance, we used this system to capture scenes with complex lighting and motion conditions that would lead to loss of information for globally-exposed cameras. These results demonstrate the advantage of pixel-wise adaptive.
• article_number: 9016128
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9016128
• html_url: https://ieeexplore.ieee.org/document/9016128/
• abstract_url: https://ieeexplore.ieee.org/document/9016128/
• publication_title: IEEE Transactions on Circuits and Systems I: Regular Papers
• conference_location:
• conference_dates:
• publication_number: 8919
• is_number: 9076766
• publication_year: 2020
• publication_date: June 2020
• start_page: 1803
• end_page: 1814
• citing_paper_count: 13
• citing_patent_count: 0
• download_count: 759
• insert_date: 20200227
• index_terms:
  • ieee_terms:
    • Image sensors
    • Dynamic range
    • Timing
    • Random access memory
    • Adaptive systems
    • Optical modulation
  • author_terms:
    • Image sensor
    • high dynamic range
    • exposure control
    • pixel-wise coded imaging
  • dynamic_index_terms:
    • Imaging System
    • Adaptive System
    • Dynamic Range
    • High Dynamic Range
    • High-dynamic-range
    • Illumination
    • Lighting
    • Light Conditions
    • Image Sensor
    • Camera Sensor
    • Optical Modes
    • Transverse Modes
    • Exposure Rate
    • Evaluation Of Exposure
    • Local Motion
    • Motion Blur
    • Brightness Variations
    • Light Intensity
    • Convolutional Neural Network
    • Flow Meter
    • Flow Measurements
    • Flow Sensor
    • Frame Rate
    • Short Exposure
    • Photocurrent
    • Optical Flow
    • Detailed System
    • PI Controller
    • Proportional Integral Controller
    • Proportional-integral Controller
    • Static Random Access Memory
    • Static Random-access Memory
    • Magnitude Of Motion
    • Frames Per Second
    • Global Exposure
    • Sample Pixels
    • Happy Faces
    • Smiley Face
    • Smiling Face
    • Continuous Motion
    • Incandescent Bulbs
    • Incandescent Light Bulbs
    • Incandescent Lamps
    • Tungsten Light
    • Exposure Values
• authors:
  • Author Name: Jie Zhang
    Affiliation: Department of Brain and Cognitive Sciences, The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, USA
    Author URL: https://ieeexplore.ieee.org/author/38526890100
    ID: 38526890100
    Order: 1
    Author Affiliations:
    • Department of Brain and Cognitive Sciences, The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, USA
  • Author Name: Jonathan P. Newman
    Affiliation: Department of Brain and Cognitive Sciences, The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, USA
    Author URL: https://ieeexplore.ieee.org/author/37088409721
    ID: 37088409721
    Order: 2
    Author Affiliations:
    • Department of Brain and Cognitive Sciences, The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, USA
  • Author Name: Xiao Wang
    Affiliation: Department of Computer Science, Boston University, Boston, USA
    Author URL: https://ieeexplore.ieee.org/author/37086500616
    ID: 37086500616
    Order: 3
    Author Affiliations:
    • Department of Computer Science, Boston University, Boston, USA
  • Author Name: Chetan Singh Thakur
    Affiliation: Department of Electronic Systems Engineering, Indian Institute of Science, Bengaluru, India
    Author URL: https://ieeexplore.ieee.org/author/37085432865
    ID: 37085432865
    Order: 4
    Author Affiliations:
    • Department of Electronic Systems Engineering, Indian Institute of Science, Bengaluru, India
  • Author Name: John Rattray
    Affiliation: Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, USA
    Author URL: https://ieeexplore.ieee.org/author/38192240400
    ID: 38192240400
    Order: 5
    Author Affiliations:
    • Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, USA
  • Author Name: Ralph Etienne-Cummings
    Affiliation: Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, USA
    Author URL: https://ieeexplore.ieee.org/author/38271387300
    ID: 38271387300
    Order: 6
    Author Affiliations:
    • Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, USA
  • Author Name: Matthew A. Wilson
    Affiliation: Department of Brain and Cognitive Sciences, The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, USA
    Author URL: https://ieeexplore.ieee.org/author/37088410243
    ID: 37088410243
    Order: 7
    Author Affiliations:
    • Department of Brain and Cognitive Sciences, The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, USA

Image Sensor

• sensor_type: CMOS
• resolution: 256x256 pixels
• dynamic_range: Not explicitly stated
• pixel_size: 6.5 µm
• dark_current: Not specified

Optical Data

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

Performance Metrics

• frame_rate: Up to 30 FPS
• signal_to_noise_ratio: Not explicitly stated, but mentions improved SNR with pixel-wise adaptive exposure
• shutter_speed: Variable based on pixel configuration, with shortest exposure of 30 ms and longest of 240 ms
• power_consumption: 7.31 mW
• noise: Higher fixed-pattern noise due to layout technique and non-CMOS process

Applications & Benefits

• cell_imaging: Not specified
• benefits: Ability to handle scenes with large dynamic range and motion, reducing motion blur, under- and overexposure through pixel-wise adaptive control.

Supporting Organizations

• supported_by: National Eye Institute (NEI), The Louis B. Thalheimer Fund for Translational Research

Manuscript Details

• publication_date: June 2020

Relevancy Score

• score: 10
• missing_fields:
  • focal_length
  • aperture
  • field_of_view
  • distortion
  • dark_current

Processed JSON Filename

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