A 30Fps 192 192 Cmos Image Sensor With Perframe Spatialtemporal Coded Exposure For Compressive Focalstack Depth Sensing

• doi: 10.1109/JSSC.2022.3149916
• title: A 30-fps 192 × 192 CMOS Image Sensor With Per-Frame Spatial-Temporal Coded Exposure for Compressive Focal-Stack Depth Sensing
• publisher: IEEE
• isbn:
• issn: 1558-173X
• rank: 410
• access_type: LOCKED
• content_type: Journals
• abstract: In this article, we present a CMOS image sensor (CIS) for coded-exposure-based compressive focal-stack imaging. The proposed CIS has a pixel design, which includes two capacitive trans-impedance amplifiers (CTIAs) and a static random access memory (SRAM), and is capable of per-frame exposure encoding with adjustable spatiotemporal resolutions. A proof-of-concept CIS prototype with a 192 $\times $ 192 pixel array is designed and fabricated in a 0.13- $\mu \text{m}$ CMOS process with a pixel size of 12.6 $\times $ 12.6 $\mu \text{m}^{2}$ . Operating at 30 frames per second (fps), the CIS demonstrates spatial–temporal coded exposure at a maximum rate of 768 masks/frame. The column-wise 10-bit single-slope (SS) analog-to-digital converter (ADC) includes a ramp-slope adaptation feature used for power optimization. During a frame of coded exposure, a linear focal sweep is implemented by a voice-coil motor (VCM) lens mounted in front of the proposed CIS. Through the sparse reconstruction of the coded image, a focal stack consisting of a volume of defocused images is used to synthesize the scene depth map. By introducing coded exposure, the proposed on-chip compressive focal-stack imaging approach facilitates a frame-saving method for passive depth sensing in machine vision and other imaging applications.
• article_number: 9723459
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9723459
• html_url: https://ieeexplore.ieee.org/document/9723459/
• abstract_url: https://ieeexplore.ieee.org/document/9723459/
• publication_title: IEEE Journal of Solid-State Circuits
• conference_location:
• conference_dates:
• publication_number: 4
• is_number: 9781662
• publication_year: 2022
• publication_date: June 2022
• start_page: 1661
• end_page: 1672
• citing_paper_count: 10
• citing_patent_count: 0
• download_count: 2323
• insert_date: 20220301
• index_terms:
  • ieee_terms:
    • Imaging
    • Cameras
    • Modulation
    • Image coding
    • Optical sensors
    • Optical imaging
    • Random access memory
  • author_terms:
    • 3-D imaging
    • CMOS image sensor (CIS)
    • coded exposure
    • compressive sensing (CS)
    • computational camera
    • focal stack
    • machine vision
    • passive depth sensing
    • single-slope (SS) analog-to-digital converter (ADC)
  • dynamic_index_terms:
    • Image Sensor
    • Camera Sensor
    • Depth Camera
    • RGB-D Camera
    • Depth Sensor
    • 3D Camera
    • Prototype
    • Pixel Size
    • Analog-to-digital Converter
    • Analog-to-digital
    • Digital-to-analog Converter
    • Depth Map
    • Function Of Depth
    • Random Access Memory
    • Machine Vision
    • Visual Navigation
    • Image Compression
    • CMOS Process
    • Pixel Array
    • Sparse Reconstruction
    • Compression Approach
    • Static Random Access Memory
    • Static Random-access Memory
    • Time-of-flight
    • Time Of Flight
    • 3D Images
    • Power Consumption
    • Memory Cells
    • Optical Power
    • Lens Power
    • Refractive Power
    • Power Efficiency
    • Charge Transition
    • Charge Modulation
    • Output Pixel
    • Input-referred Noise
    • Fill Factor
    • Coding Patterns
    • Small Capacity
    • Small Capacitance
    • High Dynamic Range
    • High-dynamic-range
    • Conversion Gain
• authors:
  • Author Name: Yi Luo
    Affiliation: Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, Canada
    Author URL: https://ieeexplore.ieee.org/author/37071953500
    ID: 37071953500
    Order: 1
    Author Affiliations:
    • Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, Canada
  • Author Name: Shahriar Mirabbasi
    Affiliation: Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, Canada
    Author URL: https://ieeexplore.ieee.org/author/37269465100
    ID: 37269465100
    Order: 2
    Author Affiliations:
    • Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, Canada

Image Sensor

• sensor_type: CMOS
• resolution: 192x192
• dynamic_range: 51.6 dB
• pixel_size: 12.6x12.6 µm^2
• dark_current: 1.2 fA

Optical Data

• focal_length: 25.0 mm
• aperture: f/2.4
• field_of_view: N/A
• distortion: N/A

Performance Metrics

• frame_rate: 30 fps
• signal_to_noise_ratio: 62.85 dB
• sensitivity: 7.1 V/lux·s
• shutter_speed: 23.62 ms
• power_consumption: 31.5 mW
• noise: 4.2 mV

Applications & Benefits

• cell_imaging: Used for 3-D imaging applications in machine vision.
• benefits: Reduces output data rate and power dissipation.

Supporting Organizations

• supported_by: Natural Sciences and Engineering Research Council of Canada (NSERC), Huawei Technologies Canada

Manuscript Details

• publication_date: June 2022

Relevancy Score

• score: 10

Processed JSON Filename

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