Color Uniformity Correction for Diffractive Waveguide Eyepieces
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Solution Overview
Problem
Display technologies, particularly diffractive waveguide eyepieces, face challenges in achieving color uniformity across the user's field-of-view due to part-to-part variation in the local thickness profile of the eyepiece substrate and other factors, leading to significant color non-uniformity issues.
Innovation Solution
The proposed solution involves a calibration process that generates correction matrices for each pixel and color channel, which are applied to the display to improve color uniformity. This process includes capturing images of the display in a color space, performing global and local white balancing, and computing correction matrices based on weighting factors to minimize color errors and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If per-pixel correction is applied to each color channel using correction matrices, then color uniformity across the field-of-view is improved, but device complexity increases
Solution Approach 1:
The correction matrices are pre-computed during a calibration process before normal operation. The system captures images of the display for multiple color channels, performs global and local white balancing, and computes correction matrices based on weighting factors. These pre-computed matrices are then applied to correct color non-uniformity in real-time without requiring complex processing during actual display operation.
Solution Approach 2:
The patent applies different correction matrices to different regions of the display (local white balancing) rather than using a single uniform correction. Each pixel or pixel group receives customized correction based on its specific color non-uniformity characteristics, allowing precise local adjustment to achieve overall color uniformity across the field-of-view.
2Measurement precision
If correction matrices are computed using local white balancing, then color accuracy is improved, but processing time increases
Solution Approach 1:
The calibration process is divided into distinct sequential steps: capturing images for multiple color channels, performing global white balancing to obtain normalized images, and then performing local white balancing to compute correction matrices. This segmentation allows each step to be optimized independently and enables the system to stop processing once sufficient accuracy is achieved, reducing overall time while maintaining precision.
Solution Approach 2:
The system performs local white balancing on normalized images to compute correction matrices, applying correction only to the extent necessary to achieve color uniformity. The weighting factors are optimized to balance color accuracy with processing efficiency, avoiding excessive computation while still achieving the desired precision in color correction.
Data Source
AI summary
Disclosed are techniques for improving the color uniformity of a display of a display device. A plurality of images of the display are captured using an image capture device. The plurality of images are captured in a color space, with each image corresponding to one of a plurality of color channels. A global white balance is performed to the plurality of images to obtain a plurality of normalized images. A local white balance is performed to the plurality of normalized images to obtain a plurality of correction matrices. Performing the local white balance includes defining a set of weighting factors based on a figure of merit and computing a plurality of weighted images based on the plurality of normalized images and the set of weighting factors. The plurality of correction matrices are computed based on the plurality of weighted images.