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Spatial processing in color reproduction.

Li Liu1, Yongyi Yang, Henry Stark

  • 1Electrical and Computer Engineering, Illinois Institute of Technology, 3301 South Dearborn, Chicago, Illinois 60616, USA.

Journal of the Optical Society of America. A, Optics, Image Science, and Vision
|September 2, 2005
PubMed
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This study introduces adjacent color variance (ACV) to constrain color reproduction, reducing artifacts in digital images. The vector space projections (VSP) method effectively handles these material and neighborhood constraints for better color accuracy.

Area of Science:

  • Color science and digital imaging.
  • Computer vision and image processing.

Background:

  • Color reproduction is limited by material constraints (ink, light) and spatial variations.
  • Existing methods struggle with neighborhood-dependent color fidelity.

Purpose of the Study:

  • To develop a method for color reproduction under material and neighborhood constraints.
  • To introduce and apply adjacent color variance (ACV) as a novel constraint.
  • To reduce reproduction artifacts in color images.

Main Methods:

  • Investigated color reproduction with maximum additive color signal constraints.
  • Introduced adjacent color variance (ACV) for neighborhood constraints.
  • Employed vector space projections (VSP) with linearized CIE-Lab space constraints.

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Main Results:

  • Demonstrated the effectiveness of ACV bounds in reducing color reproduction artifacts.
  • Showcased the utility of VSP for constrained color reproduction.
  • Validated the approach through experimental results.

Conclusions:

  • Adjacent color variance (ACV) is an effective metric for controlling color variations in spatial neighborhoods.
  • The proposed method, utilizing VSP and ACV, improves color reproduction quality by minimizing artifacts.