Approximatedctderived Measurement Matrices For Compressed Sensing

• doi: 10.1109/ISCAS.2017.8050536
• title: Approximate-DCT-derived measurement matrices for compressed sensing
• publisher: IEEE
• isbn: 978-1-5090-1427-9
• issn: 2379-447X
• rank: 1669
• access_type: LOCKED
• content_type: Conferences
• abstract: The paper presents an algorithm to generate a series of deterministic ternary matrices, which are compatible with the new generation of CMOS image sensor (CIS), Compressed Sensing (CS) based CIS (CS-CIS). The proposed matrices are derived from the approximate DCT, hence preserving the energy compaction property as DCT does. With the proposed 2D-zigzag trimming, the limited measurements could compact most of the energy. The experiment result shows that our proposed matrix contributes a significant improvement in image quality and bitrate saving of 5.7 dB BD-PSNR increase on average comparing with the random binary matrix used in the-state-of-art CS-CIS.
• article_number: 8050536
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8050536
• html_url: https://ieeexplore.ieee.org/document/8050536/
• abstract_url: https://ieeexplore.ieee.org/document/8050536/
• publication_title: 2017 IEEE International Symposium on Circuits and Systems (ISCAS)
• conference_location: Baltimore, MD, USA
• conference_dates: 28-31 May 2017
• publication_number: 8014728
• is_number: 8049747
• publication_year: 2017
• publication_date: 28-31 May 2017
• start_page: 1
• end_page: 4
• citing_paper_count: 2
• citing_patent_count: 0
• download_count: 205
• insert_date: 20170928
• index_terms:
  • ieee_terms:
    • Discrete cosine transforms
    • Frequency measurement
    • Image reconstruction
    • Compressed sensing
    • Energy measurement
    • Image coding
  • dynamic_index_terms:
    • Measurement Matrix
    • Measurement Matrices
    • Image Quality
    • Image Sensor
    • Camera Sensor
    • Bitrate
    • Improve Image Quality
    • Discrete Cosine Transform
    • Linear Combination
    • Power Consumption
    • Frequency Response
    • Image Reconstruction
    • Iterative Reconstruction
    • Tomographic Reconstruction
    • Frame Rate
    • Frequency Components
    • Transformation Matrix
    • Transformation Matrices
    • Index Measure
    • Measurement Of Indices
    • Image Signal
    • Matrix Estimation
    • Approximate Matrix
    • Image Recovery
    • Column Element
    • Elements In Each Column
    • Analog Domain
    • Restricted Isometry Property
    • Restricted Isometry Constant
    • Basis Pursuit
• isbn_formats:
  • format: Print on Demand(PoD) ISBN, value: 978-1-5090-1427-9, isbnType: New-2005
  • format: Electronic ISBN, value: 978-1-4673-6853-7, isbnType: New-2005
• authors:
  • Author Name: Jianbin Zhou
    Affiliation: Graduate School of Information Production and Systems, Waseda University, Kitakyushu, Japan
    Author URL: https://ieeexplore.ieee.org/author/37085442696
    ID: 37085442696
    Order: 1
    Author Affiliations:
    • Graduate School of Information Production and Systems, Waseda University, Kitakyushu, Japan
  • Author Name: Dajiang Zhou
    Affiliation: Graduate School of Information Production and Systems, Waseda University, Kitakyushu, Japan
    Author URL: https://ieeexplore.ieee.org/author/37403106700
    ID: 37403106700
    Order: 2
    Author Affiliations:
    • Graduate School of Information Production and Systems, Waseda University, Kitakyushu, Japan
  • Author Name: Yoshimura Takeshi
    Affiliation: Graduate School of Information Production and Systems, Waseda University, Kitakyushu, Japan
    Author URL: https://ieeexplore.ieee.org/author/37086080218
    ID: 37086080218
    Order: 3
    Author Affiliations:
    • Graduate School of Information Production and Systems, Waseda University, Kitakyushu, Japan
  • Author Name: Satoshi Goto
    Affiliation: Graduate School of Information Production and Systems, Waseda University, Kitakyushu, Japan
    Author URL: https://ieeexplore.ieee.org/author/37279993400
    ID: 37279993400
    Order: 4
    Author Affiliations:
    • Graduate School of Information Production and Systems, Waseda University, Kitakyushu, Japan

Image Sensor

• sensor_type: CMOS
• resolution: Not explicitly mentioned in the text
• dynamic_range: Not explicitly mentioned in the text
• pixel_size: Not explicitly mentioned in the text
• dark_current: Not explicitly mentioned in the text

Optical Data

• focal_length: Not explicitly mentioned in the text
• aperture: Not explicitly mentioned in the text
• field_of_view: Not explicitly mentioned in the text
• distortion: Not explicitly mentioned in the text

Performance Metrics

• frame_rate: Not explicitly mentioned in the text
• signal_to_noise_ratio: Not explicitly mentioned in the text
• sensitivity: Not explicitly mentioned in the text
• shutter_speed: Not explicitly mentioned in the text
• power_consumption: Not explicitly mentioned in the text
• noise: Not explicitly mentioned in the text

Applications & Benefits

• cell_imaging: Not explicitly mentioned in the text
• benefits: Reduction in power consumption due to Compressed Sensing (CS) implementation in image sensing.

Supporting Organizations

• supported_by: Graduate Program for Embodiment Informatics, MEXT, Japan

Manuscript Details

• publication_date: 28-31 May 2017

Relevancy Score

• score: 8
• missing_fields:
  • resolution
  • dynamic_range
  • pixel_size
  • dark_current
  • focal_length
  • aperture
  • field_of_view
  • distortion
  • frame_rate
  • signal_to_noise_ratio
  • sensitivity
  • shutter_speed
  • power_consumption
  • noise
  • cell_imaging

Processed JSON Filename

request_4255c9f1-1c8a-487c-ba22-d9269e6fcf3f-approximatedctderived_measurement_matrices_for_compressed_sensing.json