A Superparallel Image Filtering Digitalpixelsensor Employing A Compressive Multiplication Technique

• doi: 10.1109/ICECS.2014.7049997
• title: A superparallel image filtering digital-pixel-sensor employing a compressive multiplication technique
• publisher: IEEE
• isbn: 978-1-4799-4242-8
• issn:
• rank: 1312
• access_type: LOCKED
• content_type: Conferences
• abstract: A full-pixel parallel image filtering architecture is developed based on the digital-pixel-sensor. A compressive multiplication technique is employed to accelerate the processing speed. As a result, speed-ups from 3.2 to 5.2 were achieved for Gaussian kernels ranged from 5×5 to 15×15 in scale-invariant feature transform (SIFT) algorithm. A 108 × 96-pixel sensor was designed using a 0.18 μm CMOS process in a 5 mm×5 mm chip. By simulating the sensor at 100 MHz, the image filtering times for 5×5, 7×7, and 9×9 Gaussian kernels in the SIFT algorithm are 34 μs, 49 μs, and 83 μs, respectively. Such a high processing speed is very important for achieving the real-time performance when filtering high resolution images with large kernels.
• article_number: 7049997
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7049997
• html_url: https://ieeexplore.ieee.org/document/7049997/
• abstract_url: https://ieeexplore.ieee.org/document/7049997/
• publication_title: 2014 21st IEEE International Conference on Electronics, Circuits and Systems (ICECS)
• conference_location: Marseille, France
• conference_dates: 7-10 Dec. 2014
• publication_number: 7041007
• is_number: 7049902
• publication_year: 2014
• publication_date: 7-10 Dec. 2014
• start_page: 363
• end_page: 366
• citing_paper_count: 1
• citing_patent_count: 0
• download_count: 83
• insert_date: 20150226
• index_terms:
  • ieee_terms:
    • Kernel
    • Image coding
    • Parallel processing
    • Random access memory
    • Computer architecture
    • Feature extraction
    • Image resolution
  • dynamic_index_terms:
    • Image Filtering
    • High Speed
    • Gaussian Kernel
    • Gaussian Function
    • High-resolution Images
    • Processing Speed
    • Psychomotor Speed
    • Scale-invariant Feature Transform
    • High-speed Processing
    • High Processing Speed
    • Large Kernel
    • Imaging Data
    • Parallelization
    • Parallel Computing
    • Control Signal
    • Memory Cells
    • Gaussian Filter
    • Image Sensor
    • Camera Sensor
    • Processing Elements
    • Neighboring Pixels
    • Neighborhood Pixels
    • Feature Extraction Algorithm
    • Filter Kernel
    • Digital Code
• isbn_formats:
  • format: Electronic ISBN, value: 978-1-4799-4242-8, isbnType: New-2005
• authors:
  • Author Name: Hongbo Zhu
    Affiliation: VLSI Design & Education Center (VDEC), The University of Tokyo 2–11-16 Yayoi Bunkyo-ku, Tokyo, Japan
    Author URL: https://ieeexplore.ieee.org/author/37534140300
    ID: 37534140300
    Order: 1
    Author Affiliations:
    • VLSI Design & Education Center (VDEC), The University of Tokyo 2–11-16 Yayoi Bunkyo-ku, Tokyo, Japan
  • Author Name: Kunihiro Asada
    Affiliation: VLSI Design & Education Center (VDEC), The University of Tokyo 2–11-16 Yayoi Bunkyo-ku, Tokyo, Japan
    Author URL: https://ieeexplore.ieee.org/author/37273906700
    ID: 37273906700
    Order: 2
    Author Affiliations:
    • VLSI Design & Education Center (VDEC), The University of Tokyo 2–11-16 Yayoi Bunkyo-ku, Tokyo, Japan

Image Sensor

• sensor_type: CMOS
• resolution: 108 x 96 pixels
• dynamic_range: Not specified
• pixel_size: 39.48 µm x 39.48 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: 100 MHz (operational frequency)

Applications & Benefits

• cell_imaging: Used in various feature extraction algorithms such as SIFT.
• benefits: High speed processing for real-time performance in high-resolution image filtering.

Supporting Organizations

• supported_by: VLSI Design and Education Center (VDEC), the University of Tokyo, Rohm Corporation, Toppan Printing Corporation, Synopsys, Inc., Cadence Design Systems, Inc., Mentor Graphics, Inc.

Manuscript Details

• publication_date: 7-10 Dec. 2014

Relevancy Score

• score: 8
• missing_fields:
  • quantum_efficiency
  • readout_speed
  • temporal_noise
  • fixed_pattern_noise
  • microlenses
  • on_chip_colour_filters
  • global_shutter
  • rolling_shutter
  • backside_illumination

Processed JSON Filename

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