Dynamic Grayscale Selection for Display Mura Compensation
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Solution Overview
Problem
Current demura technologies use fixed grayscales for luminance compensation, leading to inaccurate compensation and adverse effects, especially for mura visible only at specific grayscales, causing visual discomfort and reducing display quality.
Innovation Solution
A method for dynamically selecting sampling grayscales by detecting grayscales with obvious mura, adjusting luminance values, and determining optimal grayscale settings using a calculating module, luminance difference detection module, and processing module to achieve precise compensation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If fixed grayscales (10%, 30%, 70%) are used for demura compensation, then the system is simple to operate and implement, but the compensation accuracy deteriorates when mura is visible only at specific grayscales
Solution Approach 1:
The patent transforms the static fixed-grayscale demura system into a dynamic system that automatically detects and adapts to the actual mura characteristics. The system dynamically selects optimal sampling grayscales based on real-time detection results, allowing it to adapt to different display panels and mura patterns rather than relying on predetermined fixed grayscales.
Solution Approach 2:
The patent changes the parameter of sampling grayscale from fixed values (10%, 30%, 70%) to dynamically determined values. By detecting luminance differences at multiple grayscales and identifying where mura is most prominent, the system selects the grayscales that provide the best compensation accuracy for the specific display panel being calibrated.
2Device complexity
If linear operation is used to obtain compensation values for intermediate grayscales, then the calculation process is simple, but the compensation effect deteriorates for grayscales where mura is not originally visible
Solution Approach 1:
The patent performs preliminary detection at multiple grayscales to identify where mura is actually present before performing compensation. By detecting luminance differences across a range of grayscales in advance, the system determines which grayscales require compensation and uses those specific detection results as the basis for calculating compensation values, rather than blindly applying linear interpolation from fixed grayscales.
3Loss of time
If three fixed sampling grayscales are used for demura, then the detection process is quick and efficient, but the detection precision deteriorates for complex and varied mura states
Solution Approach 1:
The patent segments the grayscale range into multiple detection levels rather than using only three fixed grayscales. By detecting luminance differences at multiple grayscales (including intermediate values) and identifying which segments show mura characteristics, the system achieves more precise detection of complex mura patterns while maintaining reasonable detection time through selective sampling.
Data Source
AI summary
This application relates to a method and a structure for generating a picture compensation signal, and a restoring system. A center luminance value is obtained by means of an image capturing device; then a grayscale percentage value is set by means of a calculating module, and luminance is adjusted according to the grayscale percentage value; a luminance value is obtained by means of the image capturing device according to the grayscale percentage value; a luminance difference value is obtained by means of a luminance difference detection module; and whether the luminance difference value is less than a default value is determined by a difference determining module; if the luminance difference value is less than the default value, a grayscale percentage value is reduced by the calculating module, and comparison again; and if the luminance difference value exceeds the default value, a sampling grayscale is obtained by a processing module.