Color Control Functions for Multiprimary Displays I: Robustness Analysis and Optimization Formulations

Area of Science:

• Color Science
• Computer Vision
• Human-Computer Interaction

Background:

• Multiprimary displays offer wide gamuts but require complex color control functions (CCFs).
• Alternative CCFs exist for interior gamut colors, but variations in display primaries and observer cone sensitivities can cause rendering artifacts.
• Existing methods lack a systematic approach to analyze and ensure CCF robustness against these variations.

Purpose of the Study:

• To develop a framework for analyzing the robustness of CCFs for multiprimary displays.
• To propose analytical and numerical methods for determining robust CCFs that minimize artifacts.
• To investigate the impact of primary spectral distributions and observer variations on CCF performance.

Main Methods:

• Developed a framework incorporating a common model of human color perception to analyze CCF robustness.
• Proposed an analytical approach demonstrating linearity in tristimulus space enhances resilience and constructing an axially linear CCF.
• Developed two variational objective functions for optimizing CCFs, focusing on preserving color transitions and gray axis invariance.

Main Results:

• Linearity in tristimulus space was shown to provide resilience to variations, ensuring gray axis invariance.
• An axially linear CCF was derived, proving continuous but lacking continuous derivatives.
• Two variational objective functions were formulated for robust CCF optimization, addressing color transitions and gray axis stability.

Conclusions:

• The proposed framework enables systematic analysis of CCF robustness for multiprimary displays.
• Analytical and variational methods offer pathways to designing CCFs that are resilient to display and observer variations.
• Further algorithmic computation (Part II) is needed to derive optimal CCFs based on these objective functions.