Multi-Channel Lens Calibration Mapping for Geometric Distortion
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Solution Overview
Problem
Wearable display devices with multi-channel lenses suffer from complex geometric distortions that are difficult to calibrate effectively, leading to inconsistent image quality across channels.
Innovation Solution
A distortion calibration method and device that utilizes an image acquisition unit to capture test and reference images for each channel, calculating calibration data to generate mapping data that compensates for geometric distortions using inverse transfer functions and chromatic aberration simulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Volume of moving object
If a multi-channel lens is used to reduce optical system thickness, then device compactness is improved, but geometric distortion increases making calibration difficult
Solution Approach 1:
The patent segments the complex multi-channel calibration problem into individual channel calibrations. The eyebox is divided into multiple sub-eyeboxes, and each channel is calibrated separately by capturing test images with the camera positioned at each sub-eyebox location. This segmentation allows precise calibration of each channel's geometric distortion independently, resolving the calibration difficulty while maintaining the compact multi-channel lens structure.
Solution Approach 2:
The patent performs preliminary calibration actions by capturing test images and generating reference images before actual display operation. The calibration mapping data is pre-computed by comparing test images with simulated reference images, and this pre-established mapping is then applied during normal operation to compensate for geometric distortion, ensuring consistent image quality across all channels.
2Measurement precision
If calibration is performed for each channel separately, then calibration precision is improved, but calibration complexity increases
Solution Approach 1:
The patent uses a universal calibration approach where a single camera and set of test patterns are used to calibrate all channels. The same test image and reference image generation process is applied universally to each channel, and the calibration workflow remains consistent across channels. This universal methodology achieves high calibration precision while avoiding the need for complex channel-specific calibration procedures.
Data Source
AI summary
A distortion calibration device includes an image acquisition unit which acquires a plurality of test images generated by capturing an image, which is displayed on a display panel, for each channel of the multi-channel lens by a camera and a plurality of reference images generated for each channel with respect to the multi-channel lens and the display panel, and a mapping data generator which acquires an error per channel between the plurality of test images and the plurality of reference images with respect to each channel and generates calibration data for compensating the error per channel to generate calibration mapping data based on reference mapping data and the calibration data.