• DocumentCode
    256747
  • Title

    An integrated framework for both compression noise reduction and super-resolution

  • Author

    Seok Bong Yoo ; Kyuha Choi ; Sehyeok Park ; Jong Beom Ra

  • Author_Institution
    Dept. of Electr. Eng., KAIST, Daejeon, South Korea
  • fYear
    2014
  • fDate
    7-10 Oct. 2014
  • Firstpage
    161
  • Lastpage
    162
  • Abstract
    Even though super-resolution is a promising technique, it can cause unwanted increase of compression noises, if it is applied to an image coded with a low bit-rate. To solve this problem, we propose an integrated framework to reduce compression noises and to recover high-frequency components of a coded low-resolution image. The framework effectively combines two patch-based algorithms, a patch-matching-based 3-D filtering algorithm and an example-based super-resolution algorithm, based on the combination of 3-D transform coefficients. Experimental results demonstrate that the proposed framework successfully improves the resolution while alleviating compression noises in the images coded with low bit-rates.
  • Keywords
    data compression; filtering theory; image coding; image denoising; image matching; image resolution; transforms; 3D transform coefficient; compression noise reduction; example-based superresolution algorithm; image coded low-resolution imaging; patch-based algorithm; patch-matching-based 3D filtering algorithm; Discrete cosine transforms; Hafnium; Image coding; Image resolution; PSNR; Signal processing algorithms; compression noises; integrated framework; super-resolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Consumer Electronics (GCCE), 2014 IEEE 3rd Global Conference on
  • Conference_Location
    Tokyo
  • Type

    conf

  • DOI
    10.1109/GCCE.2014.7031117
  • Filename
    7031117