• DocumentCode
    697779
  • Title

    BV-G color-image decomposition with its application to Image Processing of a digital color camera

  • Author

    Saito, Takahiro ; Yamada, Daisuke ; Komatsu, Takashi

  • Author_Institution
    Dept. of E&I Frontiers, Kanagawa Univ., Yokohama, Japan
  • fYear
    2009
  • fDate
    24-28 Aug. 2009
  • Firstpage
    233
  • Lastpage
    237
  • Abstract
    This paper extends the BV (Bounded Variation) - G variational nonlinear image-decomposition approach, which is considered to be useful for image processing of a digital color camera, to a genuine color-image decomposition approach. For utilizing interchannel color cross-correlations, this paper introduces TV (Total Variation) norms of color differences and TV norms of color sums into the BV-G energy functionals, and then derives a denoising-type decomposition-algorithm with over-complete wavelet transform, through applying the Besov-norm approximation to the variational problem. Our method decomposes a noisy color image without producing undesirable low-frequency colored artifacts in its separated BV-component, and achieves desirable high-quality color-image decomposition, which is robust against colored random noise. Furthermore, this paper applies this color-image decomposition method to an IP (Image-Processing) - pipeline of a digital color camera, and the application enables the IP-pipeline to adjust a quality trade-off between texture sharpness and noise visibility according to user´s taste.
  • Keywords
    approximation theory; cameras; image colour analysis; image denoising; image texture; BV-G color-image decomposition; Besov-norm approximation; G variational; bounded variation; digital color camera; image processing; noise visibility; texture sharpness; variational problem; Color; Colored noise; Image color analysis; Noise measurement; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference, 2009 17th European
  • Conference_Location
    Glasgow
  • Print_ISBN
    978-161-7388-76-7
  • Type

    conf

  • Filename
    7077351