Synthesis Of High Dynamic Range Motion Blur Free Image From Multiple Captures

• doi: 10.1109/TCSI.2003.809815
• title: Synthesis of high dynamic range motion blur free image from multiple captures
• publisher: IEEE
• isbn:
• issn: 1558-1268
• rank: 3691
• access_type: LOCKED
• content_type: Journals
• abstract: Advances in CMOS image sensors enable high-speed image readout, which makes it possible to capture multiple images within a normal exposure time. Earlier work has demonstrated the use of this capability to enhance sensor dynamic range. This paper presents an algorithm for synthesizing a high dynamic range, motion blur free, still image from multiple captures. The algorithm consists of two main procedures, photocurrent estimation and saturation and motion detection. Estimation is used to reduce read noise, and, thus, to enhance dynamic range at the low illumination end. Saturation detection is used to enhance dynamic range at the high illumination end as previously proposed, while motion blur detection ensures that the estimation is not corrupted by motion. Motion blur detection also makes it possible to extend exposure time and to capture more images, which can be used to further enhance dynamic range at the low illumination end. Our algorithm operates completely locally; each pixel's final value is computed using only its captured values, and recursively, requiring the storage of only a constant number of values per pixel independent of the number of images captured. Simulation and experimental results demonstrate the enhanced signal-to-noise ratio (SNR), dynamic range, and the motion blur prevention achieved using the algorithm.
• article_number: 1196451
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1196451
• html_url: https://ieeexplore.ieee.org/document/1196451/
• abstract_url: https://ieeexplore.ieee.org/document/1196451/
• publication_title: IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
• conference_location:
• conference_dates:
• publication_number: 81
• is_number: 26932
• publication_year: 2003
• publication_date: April 2003
• start_page: 530
• end_page: 539
• citing_paper_count: 42
• citing_patent_count: 15
• download_count: 813
• insert_date: 20030429
• index_terms:
  • ieee_terms:
    • Dynamic range
    • Motion detection
    • Lighting
    • Motion estimation
    • Pixel
    • Image storage
    • CMOS image sensors
    • Photoconductivity
    • Noise reduction
    • Computational modeling
  • dynamic_index_terms:
    • Dynamic Range
    • Dynamic Imaging
    • High Dynamic Range
    • Motion Blur
    • Simulation Results
    • Exposure Time
    • Lower End
    • High End
    • Image Sensor
    • Camera Sensor
    • Image Capture
    • Still Images
    • Main Procedure
    • Low Illumination
    • Use Of Capabilities
    • Manipulation Capabilities
    • High Illumination
    • Unbiased
    • Unbiased Estimates
    • Estimation Method
    • Approximation Method
    • Digital Camera
    • Estimation Algorithm
    • Approximation Algorithm
    • Low Light
    • Recursive Algorithm
    • Recursive Call
    • Readout Noise
    • High Dynamic Range Image
    • Recursive Form
    • Optimal Estimation
    • Optimal Approximation
    • Shot Noise
    • Poisson Noise
    • Linear Approximation
    • Best Linear Unbiased Estimates
    • Linear Estimation
    • High Frame Rate
    • High Signal-to-noise Ratio
    • Recursive Estimation
    • Recursive Calculation
    • Recursive Computation
• authors:
  • Author Name: Xinqiao Liu
    Affiliation: Canesta, Inc., San Jose, CA, USA
    Author URL: https://ieeexplore.ieee.org/author/37087331874
    ID: 37087331874
    Order: 1
    Author Affiliations:
    • Canesta, Inc., San Jose, CA, USA
    • Information Systems Laboratory, Department of Electrical Engineering, University of Stanford, Stanford, CA, USA
  • Author Name: A. El Gamal
    Affiliation: Department of Electrical Engineering, University of Stanford, Stanford, CA, USA
    Author URL: https://ieeexplore.ieee.org/author/37274961200
    ID: 37274961200
    Order: 2
    Author Affiliations:
    • Department of Electrical Engineering, University of Stanford, Stanford, CA, USA

Image Sensor

• sensor_type: CMOS
• resolution: 640x2512
• dynamic_range: 85 dB
• 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

• frame_rate: 1000 fps

Applications & Benefits

• cell_imaging: High-speed capture for applications in medical devices and automotive systems.
• benefits: Increased dynamic range, enhanced SNR, and motion blur prevention in high dynamic range images.

Supporting Organizations

• supported_by: Agilent, Canon, Hewlett-Packard, Interval Research, Kodak

Manuscript Details

• publication_date: April 2003

Relevancy Score

• score: 9
• missing_fields:
  • pixel_size
  • dark_current
  • focal_length
  • aperture
  • field_of_view
  • distortion
  • signal_to_noise_ratio
  • sensitivity
  • shutter_speed
  • power_consumption
  • noise

Processed JSON Filename

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