Liquid Crystal Signal Processing for Disclination Suppression
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Solution Overview
Problem
In liquid crystal panels, disclination occurs due to lateral electric fields between adjacent pixels, causing display quality degradation, and existing corrections to reduce voltage differences between pixels can worsen the situation by increasing potential differences with other pixels.
Innovation Solution
A signal processing apparatus for liquid crystal panels that detects gray-scale differences between pixels, compares these differences, and adjusts gray-scale values to reduce the differences between adjacent pixels, ensuring post-correction electric-potential differences do not exceed pre-correction levels, thereby suppressing disclination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a correction is made on display data for one of or both of adjacent pixels between which the lateral electric field strengthens so as to reduce an applied-voltage difference between the adjacent pixels, then the lateral electric field is weakened and disclination is suppressed, but the electric-potential difference with another pixel adjacent to the other side of the certain pixel increases, worsening the disclination situation
Solution Approach 1:
The patent applies different correction strategies to different pixels based on their local context. For each pixel, it compares gray-scale differences with both adjacent pixels and applies correction only when necessary, treating each pixel's neighborhood uniquely rather than applying a uniform correction across all pixels. This localised approach prevents worsening disclination in other areas.
Solution Approach 2:
The correction process is made dynamic by continuously comparing gray-scale differences before and after correction, and by conditionally applying corrections based on whether the difference exceeds a threshold. The system adapts its correction behavior based on the specific gray-scale distribution in each pixel's neighborhood, making the correction process responsive to local conditions rather than static.
2Reliability
If gray-scale values of pixels are corrected to reduce gray-scale differences, then disclination is suppressed, but the correction process becomes complex requiring detection, comparison, and conditional adjustment of multiple gray-scale values
Solution Approach 1:
The correction process is segmented into distinct functional units: a detection unit that identifies gray-scale differences, a comparison unit that evaluates whether correction is needed, and a correction unit that applies the actual correction. This segmentation allows each unit to perform a specific function efficiently, reducing overall system complexity despite the multi-step process.
Solution Approach 2:
The system uses feedback by detecting the gray-scale differences, comparing them against threshold values, and conditionally applying corrections based on the detected conditions. This feedback mechanism ensures that corrections are applied only when necessary, avoiding unnecessary processing complexity while maintaining display quality.
Data Source
AI summary
In the case where a gray-scale difference Δ1 between a pixel 110a and a pixel 110b, a gray-scale difference Δ2 between the pixel 110b and a pixel 110c are each larger than a threshold value, and Δ1>Δ2, gray-scale values of the pixels 110a, 110b and 110c are corrected into the gray-scale value of the pixel 110b+Δ1×(1−α), the gray-scale value of the pixel 110c+Δ2×(1−α), and the gray-scale value of the pixel 110c+Δ2×β, respectively (0≦α, β≦0.5). After the correction, a gray-scale different Δ1a between the pixels 110a and 110b, and a gray-scale different Δ2a between the pixels 110b and 110c satisfy the following formulas: Δ1a>Δ1, and Δ2a>Δ2, respectively.