AMOLED Pixel Calibration Using Coarse-Fine Pattern Imaging
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Solution Overview
Problem
Modern display technologies, particularly AMOLED panels, suffer from luminance non-uniformity and defects that require precise pixel location calibration for accurate optical correction, which becomes challenging with increasing resolution and complexity.
Innovation Solution
An optical correction method involving a camera and calibration patterns with coarse and fine features is used to generate coarse and high-resolution estimates of pixel locations, enabling the creation of correction data for uniform image display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single high-resolution calibration pattern is used, then measurement precision is improved, but device complexity and processing difficulty increase
Solution Approach 1:
The calibration pattern is segmented into two distinct levels: coarse features (spaced pattern of larger elements) and fine features (spaced pattern of smaller elements). The coarse features provide a low-resolution framework for initial pixel location estimation, while the fine features embedded within each coarse feature provide high-resolution refinement. This segmentation allows the system to achieve high measurement precision without overwhelming complexity in a single monolithic pattern.
2Manufacturing precision
If higher resolution display panels are used, then product quality is improved, but pixel location calibration difficulty increases
Solution Approach 1:
The calibration approach transitions from attempting to directly measure all pixel locations in a single high-resolution step to a two-dimensional hierarchical approach. First, coarse features establish a low-resolution mapping framework across the entire panel. Then, fine features provide localized high-resolution corrections within each coarse feature region. This dimensional decomposition makes calibration of high-resolution displays feasible by breaking down the complex measurement task into manageable stages.
3Area of stationary object
If coarse features are spaced throughout the entire pattern, then measurement coverage is improved, but fine feature visibility and localization accuracy decrease
Solution Approach 1:
The calibration pattern implements local quality by concentrating fine features within localized regions defined by coarse features. Each coarse feature acts as a boundary container that encloses a specific set of fine features. This local concentration ensures that fine features remain densely packed and easily distinguishable within their local contexts, while the coarse features provide overall spatial coverage and structural framework across the entire calibration pattern area.
Data Source
AI summary
What is disclosed are systems and methods for optical correction for correcting for non-uniformity in active matrix light emitting diode device (AMOLED) and other emissive displays, using iterative processing of images of calibration patterns including features of coarse and fine granularity to successively generate a high-resolution estimate of the panel pixel locations.


