• DocumentCode
    1214698
  • Title

    A robust structure-adaptive hybrid vector filter for color image restoration

  • Author

    Ma, Zhonghua ; Wu, Hong Ren ; Qiu, Bin

  • Author_Institution
    Sch. of Comput. Sci. & Software Eng., Monash Univ., Melbourne, Vic., Australia
  • Volume
    14
  • Issue
    12
  • fYear
    2005
  • Firstpage
    1990
  • Lastpage
    2001
  • Abstract
    A robust structure-adaptive hybrid vector filter is proposed for digital color image restoration in this paper. At each pixel location, the image vector (i.e., pixel) is first classified into several different signal activity categories by applying a modified quadtree decomposition to luminance component (image) of the input color image. A weight-adaptive vector filtering operation with an optimal window is then activated to achieve the best tradeoff between noise suppression and detail preservation. Through extensive simulation experiments conducted using a wide range of test color images, the filter has demonstrated superior performance to that of a number of well known benchmark techniques, in terms of both standard objective measurements and perceived image quality, in suppressing several distinct types of noise commonly considered in color image restoration, including Gaussian noise, impulse noise, and mixed noise.
  • Keywords
    Gaussian noise; adaptive filters; brightness; filtering theory; image colour analysis; image restoration; impulse noise; quadtrees; Gaussian noise; digital color image restoration; image quality; image vector; impulse noise; luminance component; mixed noise; noise suppression; quadtree decomposition; standard objective measurements; structure-adaptive hybrid vector filter; weight-adaptive vector filtering; Color; Colored noise; Digital filters; Filtering; Gaussian noise; Image restoration; Impulse testing; Pixel; Robustness; Signal restoration; Adaptive vector filtering; digital color image restoration; modified quadtree decomposition; structure-adaptive hybrid vector filter; Algorithms; Artificial Intelligence; Color; Colorimetry; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Pattern Recognition, Automated; Signal Processing, Computer-Assisted;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/TIP.2005.857269
  • Filename
    1532300