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Related Experiment Videos

Using color histogram normalization for recovering chromatic illumination-changed images.

S C Pei1, C L Tseng, C C Wu

  • 1Department of Electrical Engineering, National Taiwan University, Taipei. pei@cc.ee.ntu.edu.tw

Journal of the Optical Society of America. A, Optics, Image Science, and Vision
|November 2, 2001
PubMed
Summary

This study introduces a new image recovery method using color histogram normalization. The algorithm effectively corrects color variations caused by changing illumination using a simplified affine model.

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Area of Science:

  • Computer Vision
  • Image Processing
  • Color Science

Background:

  • Image color histograms change with illumination.
  • These changes can be modeled by affine transformations in R-G-B coordinates.

Purpose of the Study:

  • To develop a novel image recovery method for illumination variations.
  • To propose a simplified affine model for efficient color histogram normalization.

Main Methods:

  • Utilizing the covariance matrix of R-G-B color histograms.
  • Applying tensor theories and linear algebra for affine transformation estimation.
  • Developing a simplified affine model focusing on translation, scaling, and rotation.

Main Results:

  • The proposed color histogram normalization algorithm effectively recovers images under varied illumination.

Related Experiment Videos

  • The simplified affine model outperforms the general affine model in noise-sensitive scenarios.
  • The method shows effectiveness on both simulated and real images.

    • Conclusions:

    • The novel algorithm provides a robust solution for image recovery under illumination changes.
    • The simplified affine model offers improved performance and stability compared to general models.