Optimal Threshold Design For Quanta Image Sensor

• doi: 10.1109/TCI.2017.2781185
• title: Optimal Threshold Design for Quanta Image Sensor
• publisher: IEEE
• isbn:
• issn: 2573-0436
• rank: 3198
• access_type: LOCKED
• content_type: Journals
• abstract: Quanta image sensor is a binary imaging device envisioned to be the next generation image sensor after CCD and CMOS. Equipped with a massive number of single photon detectors, the sensor has a threshold q above which the number of arriving photons will trigger a binary response “1”, or “0” otherwise. Existing methods in the device literature typically assume that q = 1 uniformly. We argue that a spatial-temporally varying threshold can significantly improve the signal-to-noise ratio of the reconstructed image. In this paper, we present an optimal threshold design framework. We make two contributions. First, we derive a set of oracle results to theoretically inform the maximally achievable performance. We show that the oracle threshold should match exactly with the underlying pixel intensity. Second, we show that around the oracle threshold there exists a set of thresholds that give asymptotically unbiased reconstructions. The asymptotic unbiasedness has a phase transition behavior which allows us to develop a practical threshold update scheme using a bisection method. Experimentally, the new threshold design method achieves better rate of convergence than existing methods.
• article_number: 8169093
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8169093
• html_url: https://ieeexplore.ieee.org/document/8169093/
• abstract_url: https://ieeexplore.ieee.org/document/8169093/
• publication_title: IEEE Transactions on Computational Imaging
• conference_location:
• conference_dates:
• publication_number: 6745852
• is_number: 8287087
• publication_year: 2018
• publication_date: March 2018
• start_page: 99
• end_page: 111
• citing_paper_count: 22
• citing_patent_count: 0
• download_count: 768
• insert_date: 20171207
• index_terms:
  • ieee_terms:
    • Image reconstruction
    • Image sensors
    • Photonics
    • Prototypes
    • Dynamic range
    • Detectors
  • author_terms:
    • Quanta image sensor (QIS)
    • single-photon imaging
    • high dynamic range
    • binary quantization
    • maximum likelihood
  • dynamic_index_terms:
    • Optimal Threshold
    • Image Sensor
    • Camera Sensor
    • Quanta Image Sensor
    • Phase Transition
    • Convergence Rate
    • Convergence Speed
    • Bisection
    • Update Strategy
    • Update Scheme
    • Single-photon Detectors
    • Single Photon Detectors
    • Photon-counting Detector
    • Phase Transition Behavior
    • Phase Transition Behaviour
    • Asymptotically Unbiased
    • Markov Chain
    • Markov Process
    • Maximum Likelihood Estimation
    • Right-hand Side
    • Dynamic Range
    • Image Reconstruction
    • Iterative Reconstruction
    • Tomographic Reconstruction
    • Binary Data
    • Binary Values
    • Duty Cycle
    • Density Data
    • Storage Density
    • Goal Of This Paper
    • High Dynamic Range Image
    • Uniform Threshold
    • Single-photon Avalanche Diode
    • Single Photon Avalanche Diode
    • Incomplete Gamma Function
    • Admissible Set
    • Binary Bits
    • Secret Sharing
    • Threshold Strategy
    • Secret-sharing
    • High Dynamic Range
    • High-dynamic-range
    • Exact Optimization
    • Multiple Pixels
• authors:
  • Author Name: Omar A. Elgendy
    Affiliation: School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA
    Author URL: https://ieeexplore.ieee.org/author/37086150685
    ID: 37086150685
    Order: 1
    Author Affiliations:
    • School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA
  • Author Name: Stanley H. 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

Image Sensor

• sensor_type: Quanta Image Sensor (QIS)
• resolution: 4096x2160
• dynamic_range: Not specifically mentioned, but implies high dynamic range capabilities
• pixel_size: 200 nm pitch
• dark_current: 1-250 e- (depending on the prototype)

Optical Data

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

Performance Metrics

• frame_rate: Up to 156 k fps
• signal_to_noise_ratio: Not explicitly quantified, but improved SNR with optimal thresholds indicated
• power_consumption: Usually optimized for lower power consumption due to binary mode operations
• noise: Includes readout noise, photo-response non-uniformity, dark current, optical crosstalk and electronic crosstalk

Applications & Benefits

• cell_imaging: Utilized in medical imaging applications for its sensitivity and ability to capture low-light details
• benefits: High spatial resolution and speed enables applications in varied fields including consumer electronics, medical devices, and defense.

Supporting Organizations

• supported_by: U.S. National Science Foundation under Grant CCF-1718007

Manuscript Details

• publication_date: March 2018

Relevancy Score

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

Processed JSON Filename

request_f11507d1-624c-4027-a66e-8bca0086a649-optimal_threshold_design_for_quanta_image_sensor.json