LCH Color Space Conversion for LCD Devices
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Solution Overview
Problem
Current color conversion techniques for liquid crystal display (LCD) devices, such as model methods and neural network algorithms, are inefficient and result in significant discrepancies between displayed colors and actual object colors, failing to accurately represent colors in a way that is perceived by the human eye.
Innovation Solution
A method and apparatus for color conversion based on the LCH color space, which involves dividing the color space into two-dimensional sub-spaces, defining most saturated peripheral points, and using conversion matrices to map colors from one sub-space to another, allowing for faster and more accurate color representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If model method is used for color conversion, then conversion process can be implemented, but computation process is complicated and conversion result is not satisfactory
Solution Approach 1:
The invention divides the three-dimensional LCH color space into multiple two-dimensional color spaces by slicing along the lightness (L) axis at different intervals. Each two-dimensional color space represents a specific lightness level with chroma (C) and hue (H) as coordinates. This segmentation transforms the complex 3D color conversion problem into multiple simpler 2D conversion problems, reducing computational complexity while maintaining accuracy.
Solution Approach 2:
The invention changes the approach from general 3D color space conversion to 2D color space conversion at fixed lightness levels. By fixing the lightness parameter and converting only chroma and hue parameters in each slice, the computation becomes simpler while the overall 3D color conversion accuracy is maintained through the combination of all 2D conversion results across different lightness levels.
2Measurement precision
If neural network algorithm is used for color conversion, then conversion can be achieved, but large amount of experiments are required with long time for each experiment
Solution Approach 1:
The invention segments the color conversion task into multiple independent two-dimensional conversion tasks at different lightness levels. Each 2D conversion can be processed independently using simple conversion matrices, eliminating the need for time-consuming neural network training and experiments. This segmentation approach achieves accurate color conversion without requiring large amounts of experimental data or long training times.
3Ease of manufacture
If conventional color conversion techniques are used, then color space conversion can be performed, but large discrepancy exists between LCD color performance and actual color of object
Solution Approach 1:
The invention applies different conversion strategies to different regions of the color space by creating multiple two-dimensional color spaces at different lightness levels. Each 2D color space can have its own optimized conversion matrix based on the specific characteristics of that lightness level, allowing for more accurate local color conversion. This local optimization approach improves overall color accuracy while maintaining ease of implementation through systematic processing.
Data Source
AI summary
The present invention discloses a method and apparatus for color conversion based on LCH color space. The method includes: converting source plane Hn, Hn−1 to target plane Hn′, Hn−1′; computing Hx between Hn and Hn−1; computing Hx′ between Hn′ and Hn−1′ and at the same hue level as t Hx; computing conversion matrix Hn and Hn′; computing target color converted from color of any point of Hx and completing space color of target color. Through this method, it is possible to make the color performance closer to the actual object color or closer to expected effect than the actual object color.