Grayscale-Aware Image Sticking Compensation for Display Pixels
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing display devices apply the same compensation values for image sticking across all grayscale levels, leading to improper compensation and visible image sticking at certain levels, despite accumulating stress information.
Innovation Solution
An image sticking compensating device that calculates degradation weights based on input image data, accumulates degradation data, and determines grayscale compensation values using lookup tables or functions to optimize compensation for each pixel's age and grayscale level, considering factors like location, luminance, temperature, and emission characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the same compensation values are applied to all grayscale levels based on accumulated stress information, then the compensation process is simplified, but image sticking becomes visible at certain grayscale levels where improper compensation is performed
Solution Approach 1:
The patent segments the grayscale levels into multiple ranges (e.g., first grayscale range and second grayscale range) and applies different compensation methods to each segment. For higher grayscale levels, a first compensation value is applied, while for lower grayscale levels, a second compensation value is applied. This segmentation allows the system to maintain simplicity while improving compensation accuracy across different grayscale levels.
2Measurement precision
If grayscale compensation values are determined based on accumulated degradation data and input grayscales, then compensation accuracy across all grayscale levels is improved, but device complexity and logic design become more complex
Solution Approach 1:
The patent changes the parameter of compensation values from being uniform across all grayscale levels to being differentiated by grayscale ranges. The compensator determines different compensation values (first compensation value for higher grayscales, second compensation value for lower grayscales) based on the input grayscale level and accumulated degradation data. This parameter change enables accurate compensation across all grayscale levels while managing device complexity through systematic classification.
3Measurement precision
If degradation weights are calculated based on location, luminance, temperature, and emission characteristics, then compensation precision is improved, but calculation complexity and processing time increase
Solution Approach 1:
The patent segments the degradation calculation into multiple independent weight components: location weight, luminance weight, temperature weight, and emission weight. Each weight is calculated separately based on specific parameters (pixel location, luminance level, temperature, emission characteristics), and then combined to determine the overall degradation. This segmentation improves calculation accuracy while managing complexity by organizing the calculation process into distinct, manageable modules.
Solution Approach 2:
The patent introduces multiple parameters (location, luminance, temperature, emission characteristics) to calculate degradation weights, transforming a single-parameter degradation model into a multi-parameter model. This parameter expansion enables more accurate degradation calculation by considering various factors that affect pixel aging, while the systematic approach to parameter integration keeps the implementation manageable.
Data Source
AI summary
A image sticking compensating device according to example embodiments includes a degradation calculator configured to calculate a degradation weight based on input image data, and to calculate degradation data of a frame, an accumulator configured to accumulate the degradation data, and to generate age data using the accumulated degradation data, and a compensator configured to determine a grayscale compensation value corresponding to the age data and an input grayscale of the input image data, and to output age compensation data by applying the grayscale compensation value to the input image data.