Display Calibration Using Optical Sensor Feedback
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Solution Overview
Problem
Display systems face challenges in achieving uniform color and intensity due to artifacts such as geometric distortions, color and intensity variations, and obscuring factors like dirt and non-functional pixels, which complicate calibration and require time-consuming data collection and trade-off decisions.
Innovation Solution
A system and method for calibrating spatial intensity and color variations using optical sensor feedback, which includes iterative algorithms to converge on a target image, accounts for obscuring factors, and allows users to make trade-offs between quality factors like brightness and intensity smoothness, enabling quick recalibration without extensive new data collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional calibration methods are used to correct color and intensity variations, then display quality is improved, but calibration time and complexity increase significantly
Solution Approach 1:
The system performs preliminary characterization of display units by capturing images of a standardized chart and analyzing color and intensity variations. This preliminary data is stored and used to generate correction look-up tables, allowing rapid recalibration without repeating the entire characterization process when displays need to be recalibrated.
Solution Approach 2:
The system uses optical sensors to capture the actual display output and compares it against the target image. Based on this feedback, the system iteratively adjusts correction parameters or selects from pre-computed correction tables to achieve uniform color and intensity, significantly reducing the time required compared to traditional manual calibration methods.
2Measurement precision
If extensive data collection is performed during calibration, then measurement precision is improved, but device complexity and operation time increase
Solution Approach 1:
The system uses a standardized calibration chart as a copy of the target image properties. By measuring the deviation of the display output from this known reference copy, the system can precisely characterize color and intensity variations without requiring complex multi-step measurement procedures or multiple reference standards.
Solution Approach 2:
The calibration process is segmented into distinct phases: (1) capturing images of the calibration chart, (2) analyzing color and intensity variations across the display, (3) generating correction data, and (4) applying corrections. This segmentation allows each phase to be optimized independently and reduces overall complexity by breaking down the calibration into manageable tasks.
3Manufacturing precision
If iterative algorithms are used to converge on target image, then display quality is improved, but computation time increases
Solution Approach 1:
The system performs preliminary computation by generating multiple correction look-up tables corresponding to different possible correction scenarios. During actual recalibration, the system queries these pre-computed tables rather than performing iterative calculations in real-time, dramatically reducing recalculation time while maintaining image uniformity.
Solution Approach 2:
The iterative algorithm uses feedback from optical sensor measurements to efficiently converge on the optimal correction parameters. By comparing actual display output with the target image and adjusting corrections based on this feedback, the system achieves high image uniformity with fewer iterations than would be required without feedback guidance.
4Adaptability or versatility
If users make trade-off decisions between quality factors, then calibration flexibility is improved, but ease of operation decreases
Solution Approach 1:
The system provides self-service calibration by automatically capturing images, analyzing color and intensity variations, generating correction data, and applying corrections without requiring manual user intervention. Users simply need to point the optical sensor at the display and press a button, while the system handles the complex trade-off decisions between quality factors automatically.
Solution Approach 2:
The system uses visual feedback displayed during calibration to guide users through the process. Optical sensors capture the display output in real-time, and the system provides feedback about color and intensity uniformity, allowing users to understand the calibration progress and make informed decisions about quality trade-offs without manual measurement or complex operations.
Data Source
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AI summary
The invention provides a system and method that allows for the calibration of color and intensity in a display system in a manner that is practical for the user, and handling obscuring factors, giving the user the ability to make intelligent trade-offs, and making it possible to quickly and efficiently re-compute a correction. More generally, correction and adjustment of intensity and color non-uniformities, and using optical sensor feedback to detect and correct for those changes is contemplated. This includes, but is not limited to, showing very bright images and very dark images. This invention further provides methods for making a practical system for the user, including a method of calculating corrections, dealing with obscuring factors that can affect the calculation process, providing information to allow users to make decisions on how to make trade-offs on the quality factors of the display, and allowing fast re-calculation of intensity corrections when re-calibrating.