• DocumentCode
    3215259
  • Title

    Image super-resolution based on honey-bee mating optimization algorithm

  • Author

    Sarmadi, Saeideh ; Soroushmehr, S. M Reza ; Samavi, Shadrokh

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Isfahan Univ. of Technol., Isfahan, Iran
  • fYear
    2012
  • fDate
    15-17 May 2012
  • Firstpage
    1419
  • Lastpage
    1423
  • Abstract
    Super-resolution image reconstruction is a technique to reconstruct a high resolution image from a set of blurred and noisy low resolution images of a scene. Over recent years different methods have been introduced to increase the resolution of an image. Optimization algorithms based on swarm-intelligence have been developed and applied to various engineering fields for several decades. Process of honey bee mating has been considered as an optimization method based on insects behavior. In this paper, we propose a super-resolution method using honey bee mating optimization algorithm. The experimental results show better performance of the proposed algorithm as compared with some other super-resolution methods.
  • Keywords
    artificial intelligence; image reconstruction; image resolution; particle swarm optimisation; high resolution image reconstruction; honey-bee mating optimization algorithm; noisy low resolution images; superresolution image reconstruction; swarm-intelligence; Image resolution; Noise; Noise measurement; Optimization; Probability; Signal resolution; Yttrium; Honey-bee mating optimization; registration; resolution; super-resolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Engineering (ICEE), 2012 20th Iranian Conference on
  • Conference_Location
    Tehran
  • Print_ISBN
    978-1-4673-1149-6
  • Type

    conf

  • DOI
    10.1109/IranianCEE.2012.6292581
  • Filename
    6292581