Local Demura Processing for Display Artifact Correction
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Solution Overview
Problem
Existing display technologies suffer from artifacts such as brightness non-uniformity and pixel defects, which are not effectively addressed by current global demura algorithms, leading to degraded image quality and user discomfort, especially in AR/VR applications.
Innovation Solution
Implementing local demura algorithms that segment images into regions of interest (ROIs) and apply tailored demura processes to each ROI, using methods like low pass filtering, interpolation, and dithering to correct artifacts while preserving image sharpness and reducing computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If global demura algorithms are applied to correct display artifacts, then artifact correction is achieved, but image quality degrades and computational complexity increases
Solution Approach 1:
The patent divides the display image into multiple local regions and applies different demura algorithms to each region based on artifact characteristics. This segmentation approach reduces the computational burden compared to global processing while maintaining effective artifact correction in each localized area.
Solution Approach 2:
The patent applies different demura algorithms to different regions based on the specific artifact characteristics of each region. This local quality approach ensures that each region receives the most appropriate correction method, improving overall correction effectiveness while reducing unnecessary computational complexity in regions with fewer artifacts.
2Reliability
If global demura algorithms are applied to correct display artifacts, then artifact correction is achieved, but image sharpness deteriorates
Solution Approach 1:
By segmenting the image into local regions, the patent avoids applying uniform global corrections that blur image details. Each local region can be processed with algorithms that preserve edges and fine details while correcting artifacts, thereby maintaining image sharpness.
Solution Approach 2:
The patent selects specific demura algorithms for different regions based on their artifact characteristics, allowing regions with high-frequency content (edges, text) to use algorithms that preserve sharpness while still correcting artifacts effectively.
3Device complexity
If local demura algorithms are applied to different regions, then image sharpness is preserved and computational complexity is reduced, but correction effectiveness varies across regions
Solution Approach 1:
The patent addresses this by selecting different demura algorithms for different regions based on their specific artifact characteristics. This ensures that each region receives the most appropriate correction method, maintaining high correction effectiveness while preserving image sharpness and reducing computational complexity.
Solution Approach 2:
The patent dynamically selects demura algorithms based on the characteristics of each region, making the correction process adaptive rather than static. This dynamic approach ensures optimal correction effectiveness for each region while maintaining overall system efficiency.
Data Source
AI summary
Implementations of local demura algorithms for correcting display artifacts are provided. One aspect includes a method comprising: receiving image data; segmenting the image data into a plurality of regions of interest; applying a plurality of demura algorithms to the plurality of regions of interest to generate a plurality of corrected regions of interest by at least: applying a first demura algorithm to a first region of interest; and applying a second demura algorithm different from the first demura algorithm to a second region of interest; and generating a corrected image using at least the plurality of corrected regions of interest.