Camera Imaging Through Semi-Transparent Layers With Pixel Correction
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Solution Overview
Problem
Camera systems experience interference patterns due to constructive interference, which negatively affect data quality and algorithms, particularly in setups with displays or cover glasses.
Innovation Solution
A camera system with a sensor behind a semi-transparent layer uses a pixel-by-pixel correction to suppress interference patterns by applying a correction matrix based on calibration and parameterized models, considering distance and temperature dependencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a sensor is arranged behind a semi-transparent layer (e.g., display or cover glass), then the camera system can capture images through the layer, but interference patterns (ring-shaped fringes) are generated that negatively affect data quality
Solution Approach 1:
The system performs a calibration step before actual imaging to determine a correction matrix that characterizes the interference pattern. This preliminary characterization allows the interference to be compensated for in subsequent images, enabling the sensor to capture images through the semi-transparent layer while maintaining data quality.
Solution Approach 2:
The system changes parameters (distance to object, temperature) and records how the interference pattern varies with these parameters. By storing correction matrices for different parameter combinations, the system can adapt to different imaging conditions and maintain measurement precision across varying scenarios.
2Measurement precision
If a pixel-by-pixel correction matrix is applied to suppress interference patterns, then data quality is improved, but device complexity increases due to calibration and correction processing
Solution Approach 1:
The complex correction matrix calculation is performed in advance during a calibration step, rather than in real-time during image capture. This preliminary computation stores the complexity in a pre-computed lookup table that can be efficiently applied during actual imaging, reducing real-time processing complexity while maintaining measurement precision.
Solution Approach 2:
Instead of performing complex real-time calculations to suppress interference patterns, the system creates a copy of the interference pattern characteristics in the form of a correction matrix during calibration. This copied representation is then applied to correct images, simplifying the processing during actual use while maintaining data quality.
3Adaptability or versatility
If the camera system captures images at different distances and temperatures, then the correction can be optimized for various conditions, but the amount of calibration data and processing required increases
Solution Approach 1:
The system performs comprehensive calibration across multiple distances and temperatures in advance, storing correction matrices for various conditions. This preliminary action ensures that when actual imaging occurs, the appropriate pre-computed correction can be quickly selected and applied, optimizing adaptability while minimizing real-time calibration time.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Effectively removes interference fringes from captured data, enhancing data quality and algorithm performance by compensating for interference-induced amplitude fluctuations.
Implementation Method 1
constructive interference can create ring-shaped fringe patterns
Data Source
AI summary
A camera system includes a sensor having a plurality of pixels sensitive to electromagnetic radiation; and an evaluator. The sensor is arranged behind a semi-transparent layer. The evaluator is configured to suppress an interference pattern occurring on the sensor by a pixel-by-pixel correction.