Single Image Super Resolution Using Subband Coder And Adaptive Filtering

• doi: 10.1109/CCUBE.2017.8394133
• title: Single image super resolution using sub-band coder and adaptive filtering
• publisher: IEEE
• isbn: 978-1-5386-0616-2
• issn:
• rank: 3568
• access_type: LOCKED
• content_type: Conferences
• abstract: Super Resolution (SR) algorithm produces a high resolution (HR) image from single or multiple low resolution (LR) images. This algorithm is used to overcome the limitation of imaging CMOS sensors. It is difficult to obtain a HR image by reducing the size of the sensor after a certain limit. SR technique is used in many visual applications like biological imaging, military applications and forensic investigations. It is basically an inexpensive process to enhance the resolution of an image and to extract the high-frequency information. Two different adaptive schemes are proposed here. First one focuses on minimizing the error between the actual image and the estimated image. Resolution enhancement is done here by simultaneously modeling a blurring filter to capture the degradation process as well as modeling an innovation filter to remove the blurring effects, sensor noise using adaptive Least Square technique. The second scheme incorporates the advantages of both visual quality improvement as well as the increase in PSNR by jointly using wavelet transforms and adaptive normalized Least Mean Square (NLMS) technique. Results and performances of these novel techniques are compared with other available Super Resolution methods in terms of the visual quality index like PSNR, SSIM. Numerical results indicate that these computationally efficient single image super resolution techniques are very effective in real life imaging applications as a significant improvement of visual quality is observed in the super resolved image.
• article_number: 8394133
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8394133
• html_url: https://ieeexplore.ieee.org/document/8394133/
• abstract_url: https://ieeexplore.ieee.org/document/8394133/
• publication_title: 2017 International Conference on Circuits, Controls, and Communications (CCUBE)
• conference_location: Bangalore, India
• conference_dates: 15-16 Dec. 2017
• publication_number: 8385420
• is_number: 8394127
• publication_year: 2017
• publication_date: 15-16 Dec. 2017
• start_page: 181
• end_page: 186
• citing_paper_count: 0
• citing_patent_count: 0
• download_count: 97
• insert_date: 20180625
• index_terms:
  • ieee_terms:
    • Image resolution
    • Adaptation models
    • Image reconstruction
    • Discrete wavelet transforms
    • Technological innovation
  • author_terms:
    • Sub-band coder
    • Discrete wavelet transform (DWT)
    • Normalized Least Mean Square (NLMS) Technique
    • Single Image Super Resolution (SISR)
    • Structural Similarity (SSIM)
    • Redundant Wavelet Transform (RWT)
  • dynamic_index_terms:
    • Single Image
    • Super-resolution
    • Super-resolution Imaging
    • Adaptive Filter
    • Single Image Super-resolution
    • Low Resolution
    • Computational Efficiency
    • High-resolution Images
    • Image Resolution
    • Wavelet Transform
    • Wavelet Coefficients
    • Visual Quality
    • Actual Image
    • Low-resolution Images
    • Single Resolution
    • Forensic Investigations
    • Crime Investigation
    • Forensic Examination
    • Biological Imaging
    • Sensor Noise
    • Least Mean Square
    • Super-resolution Techniques
    • Resolution Enhancement
    • High Frequency Information
    • Blur Filter
    • Stationary Wavelet Transform
    • Undecimated Wavelet Transform
    • Optimal Filter
    • Minimum Mean Square Error
    • Image Size
    • Spatial Resolution
    • Original Image Size
    • High Visual Quality
    • Filter Weights
    • Minimum Mean Square
• isbn_formats:
  • format: Print on Demand(PoD) ISBN, value: 978-1-5386-0616-2, isbnType: New-2005
  • format: Electronic ISBN, value: 978-1-5386-0615-5, isbnType: New-2005
• authors:
  • Author Name: Milton Mondal
    Affiliation: Department of Electrical Engineering, Indian Institute of Technology, Delhi
    Author URL: https://ieeexplore.ieee.org/author/37086407365
    ID: 37086407365
    Order: 1
    Author Affiliations:
    • Department of Electrical Engineering, Indian Institute of Technology, Delhi
  • Author Name: S.D. Joshi
    Affiliation: Department of Electrical Engineering, Indian Institute of Technology, Delhi
    Author URL: https://ieeexplore.ieee.org/author/37273462600
    ID: 37273462600
    Order: 2
    Author Affiliations:
    • Department of Electrical Engineering, Indian Institute of Technology, Delhi

Image Sensor

• sensor_type: CMOS
• resolution: Not specified
• dynamic_range: Not specified
• 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

Applications & Benefits

• cell_imaging: Not specified
• benefits: Enables digital imaging in a variety of applications such as smartphones, medical devices, automotive systems.

Supporting Organizations

• supported_by: Not specified

Manuscript Details

• publication_date: 15-16 Dec. 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
  • supported_by

Processed JSON Filename

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