Display Panel Calibration Using Distance-Based Vector Volume
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Solution Overview
Problem
Existing display technologies face challenges in achieving precise calibration across different manufacturing processes and geographic locations, leading to variations in brightness and color accuracy.
Innovation Solution
A system and method for calibrating display panels using calibration vectors defined by a source pixel, a vector volume, and a calibration range, which calculates a distance between pixels to be calibrated and the source pixel to determine a calibration amount and apply it for precise calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional calibration methods are used, then display panels can be calibrated to meet display standards, but manufacturing precision and calibration consistency vary across different production processes and geographic locations
Solution Approach 1:
The calibration system is segmented into modular components: a calibration standard display device, a measurement device, and a controller that processes calibration data. This segmentation allows each component to be optimized independently and facilitates consistent calibration across different manufacturing locations by using the same modular architecture.
Solution Approach 2:
A calibration lookup table (LUT) is introduced as an intermediary data structure that stores pre-computed calibration parameters. This intermediary enables consistent calibration results by retrieving pre-calculated values rather than performing complex real-time calculations, thereby improving manufacturing precision without significantly increasing device complexity.
2Adaptability or versatility
If calibration is performed to meet different display standards for various geographic locations, then color temperature and brightness can be adjusted, but the calibration process becomes more complex and data storage requirements increase
Solution Approach 1:
The calibration data is segmented into multiple lookup tables, each corresponding to a specific display standard (e.g., NTSC, PAL, SECAM, RGB). This segmentation allows the system to store and retrieve calibration data for different geographic locations and standards efficiently, improving adaptability while managing data volume through organized storage structures.
Solution Approach 2:
Calibration parameters for different display standards are pre-computed and stored in lookup tables during system initialization or setup. This preliminary action eliminates the need for complex real-time calculations when switching between standards, reducing the effective data processing burden and enabling quick adaptation to different geographic locations.
3Measurement precision
If detailed calibration parameters are stored for each pixel, then calibration precision is improved, but data storage requirements and processing time increase
Solution Approach 1:
Calibration parameters are pre-computed for a set of representative pixels and stored in lookup tables during an initial calibration process. During actual operation, the system retrieves pre-computed values from these tables rather than performing time-consuming real-time calculations, thereby maintaining high measurement precision while significantly reducing calibration processing time.
Solution Approach 2:
Instead of storing detailed calibration parameters for every single pixel in the display array, the system creates a simplified representation using lookup tables that contain calibration data for representative pixels. This copying approach maintains sufficient calibration precision for practical purposes while dramatically reducing data storage requirements and processing time.
Data Source
AI summary
The present disclosure provides a system and method for calibrating a display panel. The system includes a display panel including a pixel array and a controller. The processor is configured to, upon executing instructions: define a calibration vector with a source pixel, a vector volume, and a calibration range; calculate a distance between a pixel to be calibrated and the source pixel; calculate a calibration amount based on the distance and the vector volume; and calibrate the pixel to be calibrated based on the calibration amount and the calibration vector.