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Enabling High Grayscale Resolution Displays and Accurate Response Time Measurements on Conventional Computers
06:50

Enabling High Grayscale Resolution Displays and Accurate Response Time Measurements on Conventional Computers

Published on: February 29, 2012

Improving gamut mapping color constancy.

G Finlayson1, S Hordley

  • 1Sch. of Inf. Syst., East Anglia Univ., Norwich, UK. graham@sys.uea.ac.uk

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 12, 2008
PubMed
Summary
This summary is machine-generated.

This study simplifies color constancy algorithms by proving 3-D information is lost in 2-D chromaticity mapping, validating the simpler 2-D approach. It also introduces a new method to enforce illumination constraints during mapping selection for improved results.

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Area of Science:

  • Computer Vision
  • Digital Photography
  • Color Science

Background:

  • Estimating scene illuminant color (color constancy) is crucial for accurate image processing.
  • The gamut mapping algorithm is a successful approach, but 2-D chromaticity versions lose intensity information and suffer from perspective distortion.

Purpose of the Study:

  • To demonstrate that only intensity information is lost in 2-D chromaticity mapping compared to 3-D.
  • To show the equivalence of 3-D and 2-D feasible sets, validating the simpler 2-D algorithm.
  • To develop an improved gamut mapping algorithm that incorporates illumination constraints during selection.

Main Methods:

  • Formal proof showing the projection of the 3-D feasible set onto 2-D is identical to the 2-D feasible set.
  • Extension of gamut mapping to incorporate illumination constraints without explicit set intersection.
  • Testing the new algorithm with real and synthetic image data.

Main Results:

  • The 3-D and 2-D gamut mapping algorithms yield equivalent feasible sets, confirming no loss of mapping information beyond intensity.
  • Perspective distortion in 2-D mapping is a significant issue, necessitating a return to 3-D for sensible selection.
  • The novel algorithm effectively enforces illumination constraints during the selection process.

Conclusions:

  • The 2-D gamut mapping algorithm is sufficient for characterizing feasible illuminants, simplifying previous methods.
  • Explicitly mapping back to 3-D is necessary to mitigate perspective distortion and enable sensible mapping selection.
  • The new algorithm achieves excellent color constancy by effectively integrating illumination constraints.