OLED Display Afterimage Prevention via Preprocessor Modulation
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Solution Overview
Problem
Organic light-emitting display (OLED) devices suffer from afterimages and display quality deterioration due to uneven deterioration of transistors or light-emitting diodes over time, leading to burn-in issues, which reduces their reliability and display quality.
Innovation Solution
A display device with a preprocessor that converts image data into separate components for the center and border areas, using HSV data modulation and deep neural networks to differentiate and emphasize afterimage components, thereby reducing false detection and enhancing detection performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If the same image is continuously displayed in a certain display area, then the display device can maintain consistent image output, but the transistors or light-emitting diodes in that area deteriorate unevenly compared to adjacent areas
Solution Approach 1:
The system performs preliminary detection of afterimage components in the current image and pre-compensates by adjusting the luminance of corresponding pixels in the next image before display. This proactive approach prevents afterimage formation by equalizing the cumulative luminance exposure across different display areas before deterioration occurs, rather than waiting for visible afterimages to appear.
2Measurement precision
If traditional afterimage detection methods are used, then the system can identify afterimage components, but false detection occurs reducing detection accuracy
Solution Approach 1:
The system employs a feedback mechanism where the detected afterimage component information from the current image is fed forward to adjust the display parameters of the next image. This closed-loop approach continuously refines detection accuracy by using actual display effects as feedback, reducing false detections through iterative optimization of detection thresholds and compensation parameters.
Solution Approach 2:
The system introduces an intermediate processing stage that analyzes the relationship between current and next images to identify afterimage components. This intermediary analysis layer separates true afterimage signals from normal image variations, reducing false detection by comparing luminance patterns across multiple frames and applying statistical filtering before final detection.
3Reliability
If the luminance of the next image is adjusted to prevent afterimage, then afterimage components are suppressed, but the overall image quality may be affected
Solution Approach 1:
The system applies luminance adjustment selectively only to pixels identified as afterimage components, leaving other pixels unchanged. This localized compensation approach prevents afterimage formation in specific problematic areas while preserving the overall image quality and visual fidelity of the rest of the display, avoiding the need to degrade the entire image.
Data Source
AI summary
The present disclosure provides a display device that includes a preprocessor, a controller, and a display panel. The preprocessor includes an area determiner outputting area data, a modulator outputting modulated data, and a synthesizer converting first image data and outputting second image data including the area data and the modulated data.