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In device-dependent color spaces, the Euclidean distance often fails to accurately represent perceived color differences, making these color spaces unsuitable for image similarity measurements. Conversely, certain device-independent color spaces, known as uniform color spaces (UCS), do align the Euclidean distance with perceived color differences. Among these, CAM16-UCS is currently considered the leading model. However, applications such as gamut mapping require additional properties, such as the preservation of planes of constant hue, which CAM16-UCS lacks. We present PCS23-UCS, a novel UCS that addresses this limitation. PCS23-UCS is specifically designed to preserve the central bundle of planes in the color space while maintaining state-of-the-art uniformity for small color differences.

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Uniform Color Space with Advanced Hue Linearity: PCS23-UCS

  • 会议论文

  • 发表日期：

    2025年

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  • Olga Basova,
  • Valentina Bozhkova,
  • Ivan Konovalenko,
  • Anastasia Sarycheva,
  • Mikhail Chobanu,
  • Valerii Timofeev,
  • Dmitry Nikolaev

摘要

In device-dependent color spaces, the Euclidean distance often fails to accurately represent perceived color differences, making these color spaces unsuitable for image similarity measurements. Conversely, certain device-independent color spaces, known as uniform color spaces (UCS), do align the Euclidean distance with perceived color differences. Among these, CAM16-UCS is currently considered the leading model. However, applications such as gamut mapping require additional properties, such as the preservation of planes of constant hue, which CAM16-UCS lacks. We present PCS23-UCS, a novel UCS that addresses this limitation. PCS23-UCS is specifically designed to preserve the central bundle of planes in the color space while maintaining state-of-the-art uniformity for small color differences.