• DocumentCode
    176072
  • Title

    Overview on image super resolution reconstruction

  • Author

    Lu Ziwei ; Wu Chengdong ; Chen Dongyue ; Qi Yuanchen ; Wei Chunping

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • fYear
    2014
  • fDate
    May 31 2014-June 2 2014
  • Firstpage
    2009
  • Lastpage
    2014
  • Abstract
    Image super resolution (SR) reconstruction technique is receiving increasing attention from the image processing community, and it has been widely used in many applications such as remote sensing image, medical image, video surveillance and high definition television. The essential of image SR reconstruction technique is how to produce a clearly high resolution (HR) image from the information of one or several low resolution (LR) images. Firstly, the fundamental idea of representative methods, the history and state of art of super resolution reconstruction are stated briefly according to the classification between the reconstruction based method and the learning based method. Secondly, advantages and defects of each methods are analyzed and summarized systematically, as well as the limitation exist in general ability. Finally, the further research directions of image super resolution reconstruction technique are proposed.
  • Keywords
    image reconstruction; image resolution; learning (artificial intelligence); high definition television; high resolution image; image SR reconstruction technique; image super resolution reconstruction technique; learning based method; low resolution images; medical image; processing community; remote sensing image; video surveillance; Face; Image edge detection; Image reconstruction; Image resolution; Imaging; Markov random fields; Noise; Comparative Analysis; Image Processing; Image Reconstruction; Regularization; Super Resolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (2014 CCDC), The 26th Chinese
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4799-3707-3
  • Type

    conf

  • DOI
    10.1109/CCDC.2014.6852498
  • Filename
    6852498