Gamut Adjusting Method for Image Display Devices
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Solution Overview
Problem
Image display devices face inaccuracies in color representation due to differences between the display gamut and standardized source gamuts like sRGB or NTSC, leading to colors outside the display gamut being unexpressed and tone mismatches when using input image signals without modification.
Innovation Solution
A gamut adjusting method and device that calculates saturation, sets a translation matrix, and performs matrix calculations to translate input image signals, using a unit matrix at low saturation, rotating with increasing saturation, and switching to maximum saturation to match the display gamut, with defined start and end translation matrices for divided hue areas to ensure accurate color representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed translation matrix is used for all saturation levels, then the device complexity is reduced, but color representation accuracy deteriorates for high saturation colors outside the display gamut
Solution Approach 1:
The patent applies dynamics by making the translation matrix variable rather than fixed. The matrix changes dynamically based on the saturation level of the input image signal, allowing optimal color mapping for different saturation ranges. This resolves the contradiction by adapting the system behavior to match the display gamut for high saturation colors while maintaining simplicity for low saturation colors.
Solution Approach 2:
The patent changes the parameter of the translation matrix based on saturation levels. Different translation matrices are selected or interpolated depending on whether the saturation is below or above a threshold value, enabling accurate color representation across the entire gamut while managing computational complexity through parameter-based adaptation.
2Adaptability or versatility
If the display gamut is fully utilized for high saturation colors, then color gamut coverage is improved, but tone accuracy deteriorates for colors that should remain within the source gamut
Solution Approach 1:
The patent applies local quality by treating different saturation ranges differently. A first translation matrix is used for low saturation colors to maintain tone accuracy, while a second translation matrix is used for high saturation colors to maximize gamut coverage. This localized approach resolves the contradiction by optimizing for different objectives in different color spaces.
Solution Approach 2:
The system dynamically switches between different translation matrices based on the saturation level of the input signal. This dynamic adaptation allows the system to maximize color gamut coverage for high saturation colors while preserving tone accuracy for low saturation colors, resolving the contradiction between these two opposing requirements.
3Measurement precision
If a single translation matrix is used for all hue areas, then the device complexity is reduced, but color mapping precision deteriorates for specific hue regions
Solution Approach 1:
The patent segments the hue area into multiple regions (first hue area and second hue area) with different translation matrices. This segmentation allows for precise color mapping in specific hue regions that require special handling due to gamut differences, while maintaining overall system manageability through structured organization of the segmentation.
Solution Approach 2:
Different translation matrices are applied to different hue areas based on their specific color mapping requirements. This local quality approach enables optimized color mapping for each hue region while organizing the complexity through systematic classification of hue areas into distinct categories.
Data Source
AI summary
A gamut adjusting method fully expresses a dynamic range of a display gamut to display an image more naturally. With respect to a brightness signal of each primary color of an input image signal, a data translation unit executes a matrix calculation based on a translation matrix for conversion into an image signal for display control. A saturation calculating unit calculates saturation of the input image signal. When saturation is smaller than a threshold value, the data translation unit is set with a translation matrix such that a tone on the display corresponds to or approximates a tone of the input image signal. When saturation is greater than the threshold value and smaller than a maximum value, as the saturation increases, a translation matrix is switched such that a vector on a xy chromaticity diagram toward a tone on a display approximates a vector toward a tone for maximum saturation.