• DocumentCode
    254476
  • Title

    Decorrelated Vectorial Total Variation

  • Author

    Ono, Shintaro ; Yamada, Isao

  • Author_Institution
    Dept. of Commun. & Comput., Tokyo Inst. of Technol. Eng., Tokyo, Japan
  • fYear
    2014
  • fDate
    23-28 June 2014
  • Firstpage
    4090
  • Lastpage
    4097
  • Abstract
    This paper proposes a new vectorial total variation prior (VTV) for color images. Different from existing VTVs, our VTV, named the decorrelated vectorial total variation prior (D-VTV), measures the discrete gradients of the luminance component and that of the chrominance one in a separated manner, which significantly reduces undesirable uneven color effects. Moreover, a higher-order generalization of the D-VTV, which we call the decorrelated vectorial total generalized variation prior (D-VTGV), is also developed for avoiding the staircasing effect that accompanies the use of VTVs. A noteworthy property of the D-VT(G)V is that it enables us to efficiently minimize objective functions involving it by a primal-dual splitting method. Experimental results illustrate their utility.
  • Keywords
    convex programming; generalisation (artificial intelligence); image colour analysis; D-VTGV; D-VTV; color effects; color images; decorrelated vectorial total generalized variation prior; decorrelated vectorial total variation prior; objective functions; primal-dual splitting method; Computer vision; Conferences; Gain; PSNR; Pattern recognition; Standards;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on
  • Conference_Location
    Columbus, OH
  • Type

    conf

  • DOI
    10.1109/CVPR.2014.521
  • Filename
    6909917