• DocumentCode
    938635
  • Title

    Local linear LUT method for spatial colour-correction algorithm speed-up

  • Author

    Gatta, C. ; Rizzi, A. ; Marini, D.

  • Author_Institution
    Dept. of Inf. Technol., Univ. of Milano, Crema, Italy
  • Volume
    153
  • Issue
    3
  • fYear
    2006
  • fDate
    6/8/2006 12:00:00 AM
  • Firstpage
    357
  • Lastpage
    363
  • Abstract
    There is a class of nonlinear filtering algorithms for digital colour enhancement, characterised by data-driven local effects and high computational cost. A new method called LLL (local linear look-up table (LUT)) is presented, which speeds up these filters without losing their local effect. Usually, classic LUT-based methods are global whereas the approach presented here uses the principles of LUT transformation in a local way. The main idea of this method is to apply the colour-enhancement algorithm to a small sub-sampled version of the input image and to use a modified look-up table technique to maintain the local filtering effect of the colour-enhancement algorithm. The method increases the speed of colour-filtering algorithms, reducing the number of pixels involved in the computation by sub-sampling the input image. To overcome possible loss of detail due to sub-sampling, an optional, additional stage to maintain high-frequency content is shown. LLL with two of these filters, the Brownian Retinex implementation and the automatic colour equalisation algorithm, are tested. Results, comparison and conclusions are presented.
  • Keywords
    filtering theory; image colour analysis; image enhancement; image sampling; nonlinear filters; table lookup; automatic colour equalisation; digital colour enhancement; image sampling; local linear look-up table technique; nonlinear filtering algorithms; spatial colour-correction algorithm; speed-up algorithm;
  • fLanguage
    English
  • Journal_Title
    Vision, Image and Signal Processing, IEE Proceedings -
  • Publisher
    iet
  • ISSN
    1350-245X
  • Type

    jour

  • DOI
    10.1049/ip-vis:20050279
  • Filename
    1633703