Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (1)
  • Open Access

    ARTICLE

    Shear Let Transform Residual Learning Approach for Single-Image Super-Resolution

    Israa Ismail1,*, Ghada Eltaweel1, Mohamed Meselhy Eltoukhy1,2

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3193-3209, 2024, DOI:10.32604/cmc.2023.043873

    Abstract Super-resolution techniques are employed to enhance image resolution by reconstructing high-resolution images from one or more low-resolution inputs. Super-resolution is of paramount importance in the context of remote sensing, satellite, aerial, security and surveillance imaging. Super-resolution remote sensing imagery is essential for surveillance and security purposes, enabling authorities to monitor remote or sensitive areas with greater clarity. This study introduces a single-image super-resolution approach for remote sensing images, utilizing deep shearlet residual learning in the shearlet transform domain, and incorporating the Enhanced Deep Super-Resolution network (EDSR). Unlike conventional approaches that estimate residuals between high and… More >

Displaying 1-10 on page 1 of 1. Per Page