LCD Tone Correction Data Preparation Device
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Solution Overview
Problem
Current white balance adjustment methods require a large number of measurement points to predict the shape of the tone characteristic curve, making them inefficient.
Innovation Solution
A tone correction data preparation device that calculates a white gamma curve based on tone deviations and measured gamma values, and uses this to determine conversion values for correcting white balance, allowing for white balance adjustment with a smaller number of measurement points by calculating three primary gamma curves and expected output values for red, green, and blue colors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a greater number of measurement points are obtained to predict the shape of the tone characteristic curve, then the accuracy of curve shape prediction is improved, but the time required for measurement and the complexity of the process increases
Solution Approach 1:
The invention changes the measurement parameters by selecting specific key points (maximum value, minimum value, intermediate value, and tone value around singular region) instead of measuring all points. This parameter selection strategy allows accurate curve prediction with fewer measurements, resolving the contradiction between measurement accuracy and time consumption.
Solution Approach 2:
The invention performs preliminary identification of singular regions in the Z stimulus value characteristic before measurement. By pre-determining where singularities occur, the measurement process can focus on critical points only, reducing overall measurement time while maintaining prediction accuracy.
2Measurement precision
If a greater number of measurement points are obtained to predict the shape of the tone characteristic curve, then the accuracy of curve shape prediction is improved, but the device complexity and processing requirements increase
Solution Approach 1:
The invention reduces device complexity by changing from a comprehensive measurement approach to a selective measurement approach. By measuring only at maximum value, minimum value, intermediate value, and singular region points, the system requires fewer measurement channels and less complex data processing infrastructure.
Solution Approach 2:
The invention extracts only the essential measurement points needed for accurate curve prediction, separating them from unnecessary measurement points. This extraction principle simplifies the measurement system by focusing resources on critical measurements only.
3Reliability
If measurement points are increased to accurately capture the tone characteristic curve shape, then the reliability of white balance adjustment is improved, but the productivity of the adjustment process decreases
Solution Approach 1:
The invention changes the measurement parameter strategy from uniform sampling to strategic sampling at critical points. By measuring at maximum value, minimum value, intermediate value, and singular regions, the system achieves reliable curve prediction with fewer points, thereby improving productivity without sacrificing reliability.
Solution Approach 2:
The invention uses feedback from the identified singular region characteristics to determine where measurements are most needed. This feedback-driven measurement strategy ensures reliable curve prediction while minimizing the number of measurements required, thus improving adjustment efficiency.
Data Source
AI summary
The driver calculates a white gamma curve based on a deviation of a tone (including a maximum tone) of white displayed on a liquid crystal display panel (LCD panel) with respect to a target tone value and on a measured gamma value at arbitrary tones excluding a maximum tone in a white gamma characteristic of the LCD panel. The driver calculates three primary gamma curves by applying, to the white gamma curve, a relation obtained by comparing a gamma curve of white of a reference display panel with gamma curves of respective red, green, and blue. The driver corrects a white balance of display data based on the three primary gamma curves and expected output values of respective three primary colors calculated based on highest tone values of three primary colors of the reference display panel and of white of the LCD panel.