AMOLED Aging Pattern Extraction via Edge Detection and Re-interpolation

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Solution Overview

Problem

Existing display technologies face challenges in efficiently estimating and compensating for aging patterns in active matrix organic light-emitting diode (AMOLED) displays, particularly in minimizing the number of pixel measurements required to achieve image uniformity and account for degradation over time.

Innovation Solution

A method involving down-sampling of pixel measurements using a measurement circuit, followed by interpolation and edge detection to refine the aging pattern, allowing for the estimation of aging characteristics with a reduced number of measurements, thereby minimizing time and variance in non-uniformity compensation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If pixel measurements are taken uniformly across the entire display, then measurement precision is improved, but measurement time and device complexity increase

Engineering Contradiction:

Improveaging pattern estimation accuracyVSAvoidmeasurement time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The display is divided into multiple regions of interest (ROIs) based on detected edge locations. Measurements are concentrated in these ROI regions rather than uniformly across the entire display, reducing the total number of measurements while maintaining accuracy in critical areas where aging patterns are most prominent.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Different measurement strategies are applied to different regions of the display. Edge regions and ROI areas receive denser measurement sampling, while non-critical regions use coarser sampling. This local differentiation optimizes measurement precision where needed while reducing overall measurement time.

Inventive Principle:

Principle #3Local quality

2Productivity

If the number of pixel measurements is reduced, then measurement time is decreased, but measurement precision deteriorates

Engineering Contradiction:

Improvecompensation efficiencyVSAvoidaging characteristic accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

Edge detection is performed as a preliminary step before conducting the actual pixel measurements. This preliminary action identifies critical regions where measurements are most needed, allowing the subsequent measurement process to focus resources efficiently and maintain precision with fewer total measurements.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

Regions of interest (ROIs) act as intermediaries between the edge detection results and the final pixel measurements. The ROIs are determined based on edge locations and serve as the target areas for concentrated measurement, bridging the gap between reduced measurement numbers and maintained precision.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Manufacturing precision

If edge detection and re-interpolation algorithms are applied, then manufacturing precision is improved, but device complexity increases

Engineering Contradiction:

Improveaging pattern extraction accuracyVSAvoidprocessing algorithm complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

Complex physical measurement of all pixels is replaced with a combination of selective physical measurements and computational algorithms. Edge detection and re-interpolation algorithms process the limited measured data to reconstruct the complete aging pattern, substituting computational complexity for reduced physical measurement complexity.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Loss of time

If measurements are concentrated in specific regions, then measurement time is reduced, but coverage area decreases

Engineering Contradiction:

Improvemeasurement timeVSAvoidmeasurement coverage area

Core Design Contradiction:

Loss of timeVSArea of stationary object

Solution Approach 1:

The measurement strategy transitions from uniform two-dimensional coverage to a hierarchical approach where edge detection identifies critical one-dimensional boundary regions, and ROI analysis further refines the measurement areas. This dimensional refinement allows concentrated measurements to capture the most significant aging information.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Data Source

PatentUS10789867B2Re-interpolation with edge detection for extracting an aging pattern for AMOLED displays

Publication Date: 2020.09.29 IGNIS INNOVATION

AI summary

A method that includes an initial uniform pixel measurement and interpolation followed by an edge detection algorithm to recognize the areas that contribute mostly to the estimation error due to the interpolation. The pixels on the detected edges and around their vicinity are also measured, and an aging pattern of the entire display is obtained by re-interpolating the entire measured set of data for the initially measured pixels as well as the pixels around the detected edges. The estimation error is reduced particularly in the presence of aging patterns having highly spatially correlated areas with distinctive edges.