Using Perceptual Color Contrast for Color Image Processing

  • Guangming Xiong
  • Dah-Jye Lee
  • Spencer G. Fowers
  • Jianwei Gong
  • Huiyan Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6455)


Many grayscale image processing techniques such as edge and feature detection, template matching, require the computations of image gradients and intensity difference. These computations in grayscale are very much like measuring color difference between two colors. The goal of this work is to determine an efficient method to represent color difference so that many existing grayscale image processing techniques that require the computations of intensity difference and image gradients can be adapted for color without significantly increasing the amount of data to process and without significantly altering the grayscale-based algorithms. In this paper, several perceptual color contrast measurement formulas are evaluated to determine the most applicable metric for color difference representation. Well-known edge and feature detection algorithms using color contrast are implemented to prove its feasibility.


Color Difference Image Gradient Edge Strength Harris Corner Detector Color Image Processing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Guangming Xiong
    • 1
  • Dah-Jye Lee
    • 2
  • Spencer G. Fowers
    • 2
  • Jianwei Gong
    • 1
  • Huiyan Chen
    • 1
  1. 1.School of Mechanical EngineeringBeijing Institute of TechnologyBeijingChina
  2. 2.Dept. of Electrical and Computer EngineeringBrigham Young UniversityProvoUSA

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