RGBW Color Space Conversion Using Triangular Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing color conversion systems for multi-primary displays, such as RGBW, face challenges in accurately converting colors between different color spaces, particularly when the white primary is positioned at the white-point, leading to issues with gamut limitations and color representation.
Innovation Solution
The system divides the CIE chromaticity diagram into three triangles using RGBW primaries and calculates specific matrices to linearly interpolate white values, allowing for conversion between RGBW and CIE XYZ color spaces, with additional matrices for handling out-of-gamut colors by preserving hue through clamping and scaling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the white primary is positioned at the white-point in RGBW color space, then the color conversion accuracy is improved, but the gamut representation becomes limited
Solution Approach 1:
The chromaticity diagram is divided into multiple triangular regions, each with its own conversion matrix. This segmentation allows the system to handle different color regions separately, improving accuracy within each triangle while collectively covering a broader gamut across all regions.
Solution Approach 2:
Different conversion matrices are applied to different triangular regions of the chromaticity diagram. Each matrix is optimized for its specific region, providing locally optimal color conversion accuracy while collectively addressing the broader gamut representation issue.
2Device complexity
If standard color conversion matrices are used for RGBW, then the conversion process is simplified, but out-of-gamut colors cannot be correctly represented
Solution Approach 1:
The color space is divided into multiple triangular regions, each with dedicated conversion matrices. This segmentation ensures that out-of-gamut colors in any region can be correctly represented by the appropriate matrix, maintaining reliability without requiring a single complex universal matrix.
Solution Approach 2:
The chromaticity diagram is pre-divided into triangular regions and corresponding matrices are pre-calculated and stored. When conversion is needed, the system simply selects the appropriate pre-computed matrix based on the color's location, maintaining simplicity while ensuring correct out-of-gamut handling.
3Measurement precision
If hue preservation is prioritized for out-of-gamut colors, then color accuracy is improved, but luminosity differences become more noticeable
Solution Approach 1:
The conversion matrices are specifically designed to preserve hue parameters for out-of-gamut colors by adjusting the transformation coefficients. This parameter optimization ensures accurate hue representation while the patent acknowledges and manages the resulting luminosity variations as a separate consideration.
Data Source
AI summary
Systems and methods are disclosed to effect conversion of a three color primary image data set to a multiple color primary set in which one of the primaries is white. One method converts a three-color image data set comprising C1, C2, and C3 colors into a four-color image data set comprising C1, C2, C3 and W colors.