Pixel Correction Masks for Display Non-Uniformity
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Solution Overview
Problem
Artificial reality systems face challenges in correcting dead pixels due to manufacturing inaccuracies and optical distortions, which affect the alignment and uniformity of light-emitting elements across color channels, leading to suboptimal visual effects.
Innovation Solution
A system that uses customized pixel correction masks based on optical measurements to adjust pixel values in real-time, applying masks to pixels of the same visual location rather than relative positions in the array, and interpolating correction masks for improved alignment and distortion compensation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional dead pixel correction methods are used, then the correction process is simple, but the visual effect is suboptimal due to misalignment and optical distortions
Solution Approach 1:
The patent applies different correction masks to different color channels (red, green, blue) based on their specific non-uniformity characteristics. Each color channel receives a customized mask that accounts for its unique pixel alignment and optical properties, rather than using a single uniform correction approach for all channels.
Solution Approach 2:
The system performs optical measurements during the manufacturing stage to capture the actual positions and characteristics of light-emitting elements before final assembly. This preliminary characterization data is stored and used to generate correction masks in advance, enabling accurate compensation without requiring complex real-time adjustments.
2Measurement precision
If pixels are corrected based on relative positions in pixel arrays, then the correction is straightforward, but misalignment and optical distortions degrade image quality
Solution Approach 1:
The system uses optical measurements taken during manufacturing to accurately determine the real positions of light-emitting elements in viewer space. This feedback information about actual pixel locations is then used to generate correction masks that compensate for manufacturing variations and optical distortions, achieving precise correction despite manufacturing imperfections.
Solution Approach 2:
The patent transforms the correction approach from using relative pixel array positions (2D grid coordinates) to using viewer space positions (optical coordinates). This dimensional transformation allows the system to account for optical distortions and achieve accurate pixel mapping that reflects how pixels actually appear to the viewer rather than their physical array positions.
3Adaptability or versatility
If a single correction mask is used for all color channels, then the system is simple, but it cannot account for different non-uniformity factors of each channel
Solution Approach 1:
The patent applies different correction masks to different color channels (red, green, blue) based on their specific non-uniformity characteristics. Each color channel receives a customized mask that accounts for its unique pixel alignment and optical properties, rather than using a single uniform correction approach for all channels.
Data Source
AI summary
In one embodiment, a computing system may access a first value associated with a first pixel of the first color channel from a first bitmap associated with a first color channel. The system may select a first mask comprising a plurality of first scaling factors based on the first value of the first bitmap. The system may access a second value associated with a second pixel of the second color channel from a second bitmap associated with a second color channel. The system may select a second mask comprising a plurality of second scaling factors based on the second value of the second bitmap. The system may modify each of first and second component values of the corresponding color channel using the corresponding plurality of scaling factors of the corresponding mask. The system may output the modified first and second component values to a display.