Head-Mounted Display Image Correction Using Multiple Distortion Parameters
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Solution Overview
Problem
Existing methods for correcting image distortion caused by lens optical distortion in display devices are limited, as a single distortion function cannot effectively correct images across different display devices with varying optical distortion amounts.
Innovation Solution
A method for image correction that involves obtaining a test image, calculating the coordinates of its center point, determining multiple distortion amounts and corresponding distortion coefficients, and using these to calculate and correct the actual deformation of the image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single distortion function is used for image correction, then the correction process is simple, but the correction accuracy deteriorates because different lenses have different optical distortion amounts
Solution Approach 1:
The patent divides the image correction process into multiple stages: first measuring optical distortion offset data for each sub-pixel, then calculating a distortion function, and finally applying the correction. This segmentation allows the system to handle different lens distortion characteristics systematically while maintaining computational efficiency.
Solution Approach 2:
The patent introduces multiple distortion parameters including distortion offset data for each sub-pixel, distortion function parameters, and correction parameters. By changing and optimizing these parameters based on actual measured data, the system achieves high correction accuracy across different lens types without excessive complexity.
2Measurement precision
If optical distortion offset data is measured for each sub-pixel, then the correction accuracy is improved, but the measurement time and processing complexity increase
Solution Approach 1:
The patent performs optical distortion offset data measurement during the development stage of display devices, before the actual image correction is needed. This preliminary measurement allows the distortion function to be pre-calculated and stored, so that during normal operation, only the application of the pre-computed correction is required, significantly reducing real-time processing time.
Solution Approach 2:
The patent creates a digital model (distortion function) that copies the optical distortion characteristics of the lens. Instead of measuring distortion in real-time for each image, the system uses the pre-measured and stored distortion function to correct images, eliminating the need for repeated time-consuming measurements.
3Ease of manufacture
If a distortion function is set at the system side during development, then the correction implementation is simplified, but the adaptability to different lenses with varying optical distortion amounts is reduced
Solution Approach 1:
The patent enables the system to automatically measure its own optical distortion characteristics and calculate its specific distortion function. Instead of relying on pre-set system-side distortion functions that may not match the actual lens, the system performs self-measurement and self-correction, adapting to its specific lens characteristics while maintaining ease of implementation through automated processes.
Solution Approach 2:
The patent allows the distortion function parameters to be dynamically adjusted based on actual measured optical distortion offset data for each sub-pixel. This enables the system to adapt to different lens types and distortion amounts by modifying the distortion function parameters, while the automated measurement and calculation process keeps the implementation simple.
Data Source
AI summary
The present disclosure relates to a method for image correction, a head-mounted display device, and a storage medium. The method includes: obtaining a currently displayed test image when a display device is starting; calculating the coordinates of the center point of the test image; determining multiple distortion amounts and a distortion coefficient corresponding to each distortion amount; obtaining the original pixel coordinates of the target sampling points; calculating the distorted pixel coordinates of the target sampling points according to the multiple distortion amounts, the distortion coefficient corresponding to each distortion amount, and the original pixel coordinates; calculating the actual deformation of the test image; and correcting the test image according to the actual deformation.