• DocumentCode
    1861824
  • Title

    Discrete wavelet transform-based structural similarity for image quality assessment

  • Author

    Yang, Chun-Ling ; Gao, Wen-Rui ; Po, Lai-Man

  • Author_Institution
    Sch. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou
  • fYear
    2008
  • fDate
    12-15 Oct. 2008
  • Firstpage
    377
  • Lastpage
    380
  • Abstract
    Image quality assessment method plays a major role in image processing. Structural similarity (SSIM) is a novel image quality assessment method, and attracts a lot of attentions for its good performance and simple calculation. But it is proposed in pixel domain, a large computation load is introduced when using it to guide image processing algorithm in discrete wavelet transform (DWT) domain. And image processing in DWT domain has been very common. This paper proposes a discrete wavelet transform- based structural similarity (DWT-SSIM) method for image quality assessment. As it highlights human eyes´ sensitive frequency bands, the proposed measure has a better correlation with the judgment of human observers than SSIM. Furthermore, the method is easy to implement and embed in DWT domain processing algorithms.
  • Keywords
    discrete wavelet transforms; image processing; DWT domain processing algorithms; discrete wavelet transform-based structural similarity; human eye sensitive frequency bands; human observers; image processing; image quality assessment; pixel domain; Discrete wavelet transforms; Distortion measurement; Humans; Image coding; Image processing; Image quality; PSNR; Pixel; Visual system; Wavelet domain; human visual system (HVS); image processing; image quality assessment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on
  • Conference_Location
    San Diego, CA
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-1765-0
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2008.4711770
  • Filename
    4711770