Display Driving Method Reduces Side View Color Cast
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Solution Overview
Problem
Liquid crystal display devices suffer from significant color cast issues, particularly with red, green, and blue hues when viewed from the side, and exhibit greater brightness differences between front and side views as gray scale levels decrease, leading to poor image presentation.
Innovation Solution
A display driving method that divides the original gray scale data group into two groups, with the first group featuring the maximal gray scale and the second group either zero or greater than the minimal gray scale, adjusting light source intensities to reduce brightness differences and minimize color cast, by determining average gray scales and light source intensities for each hue and displaying these groups sequentially within the original display duration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the original gray scale data group is displayed directly, then the display process is simple, but the side view color cast is serious and brightness difference between front and side views is large
Solution Approach 1:
The original gray scale data group is divided into a first gray scale data group and a second gray scale data group based on average gray scales and light source intensities of different hues. This segmentation allows independent optimization of each group's display timing and intensity, enabling reduction of side view color cast and brightness difference while maintaining front view quality
Solution Approach 2:
The display system dynamically adjusts the display timing and light source intensity for different gray scale data groups based on their specific characteristics. The first gray scale data group is displayed during a first time period with first light source intensity, while the second gray scale data group is displayed during a second time period with second light source intensity, creating adaptive optimization for different content types
2Object-affected harmful factors
If the gray scale data is divided into multiple groups and displayed sequentially, then the color cast is reduced, but the display process becomes more complex
Solution Approach 1:
The system performs preliminary analysis of the original gray scale data group to calculate average gray scales and light source intensities for different hues before division. This pre-processing establishes clear criteria for separating the data into first and second gray scale data groups, automating the complex division process and reducing manual intervention requirements
Solution Approach 2:
The display system uses feedback from the calculated average gray scales and light source intensities to dynamically determine how to divide and display the gray scale data groups. The feedback mechanism allows the system to automatically adjust display parameters based on content characteristics, reducing color cast without requiring complex manual configuration
Data Source
AI summary
The present disclosure relates to a display driving method, device and apparatus, an original gray scale data group of the pixel units in the preset display area and of the content to be displayed is acquired; average gray scales of the hues in the preset display area are determined according to the original gray scale data group; original light source intensities of each of the hues in the preset display area and of the content to be displayed are acquired; the original gray scale data group is divided into a first gray scale data group and a second gray scale data group and the driving light source intensities of each of the hues in the preset display area are determined according to the original gray scale data group of the pixel units, the average gray scales of each of the hues and the original light source intensities; the gray scales of each of the hues of the first gray scale data group are the maximal gray scale in the original gray scale data group; the gray scales of each of the hues of the second gray scale data group are 0 or greater than the minimal gray scale of the original gray scale data group.