Multi-Camera Synchronization Through Dynamic White Balance
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Solution Overview
Problem
Multi-camera devices experience color inconsistencies and transitions that result in insufficient results during seamless switching between cameras due to differences in properties and characteristics, particularly in video capture scenarios.
Innovation Solution
A method for synchronizing multi-camera devices by determining achromaticity and calculating RGB-means to adapt white balance gain dynamically, using auto white balance statistics and individual color correction matrices to ensure seamless transitions between cameras, even under changing illumination conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pre-calculated inter-camera color calibration matrices are used, then color consistency between cameras can be achieved under specific illumination conditions, but the system cannot handle illuminations outside the pre-calculated range and requires extensive pre-processing data
Solution Approach 1:
The patent applies dynamics by transitioning from static pre-calibrated color correction matrices to dynamic white balance gain adaptation. The system continuously adjusts WB gains based on real-time achromaticity analysis of captured image data, allowing the color calibration to adapt to any illumination condition rather than relying on pre-calculated matrices for specific lighting scenarios.
Solution Approach 2:
The patent changes the parameter approach by shifting from fixed color correction matrices to variable white balance gains. The WB gains are dynamically adjusted based on the measured achromaticity of the scene, enabling the system to handle diverse illumination conditions by modifying the color parameters in real-time rather than relying on predetermined calibration data.
2Measurement precision
If high-resolution image data is processed for color synchronization, then accurate color matching can be achieved, but computational complexity and processing time increase significantly
Solution Approach 1:
The patent extracts only the essential information needed for color synchronization by focusing on achromaticity measurement rather than processing the entire high-resolution image data. By isolating and analyzing only the achromatic components of the scene, the system achieves accurate color matching while significantly reducing computational complexity and processing requirements.
Solution Approach 2:
The patent applies partial action by processing only the necessary portion of image data for color synchronization - specifically the achromaticity information - rather than analyzing all image parameters. This selective processing approach maintains color matching accuracy while minimizing computational overhead and enabling real-time operation.
3Adaptability or versatility
If dynamic white balance adaptation is implemented, then seamless camera switching can be achieved under varying illumination, but real-time processing requires efficient algorithms to minimize delay
Solution Approach 1:
The patent applies preliminary action by pre-establishing the achromaticity analysis framework and white balance adaptation mechanism. The system is prepared to handle illumination changes by having the achromaticity measurement and WB gain adjustment algorithms ready and optimized in advance, enabling real-time response when camera switching occurs under varying lighting conditions without significant processing delay.
Data Source
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AI summary
Method for synchronization of a multi-camera device having a first camera providing first image data and a second camera providing second image data, including: Determine achromaticity of the first image data and the second image data; Calculate RGB-means for the first image data and the second image data as weighted average of the RGB-values of the first image data and second image data on the basis of achromaticity; Adapting a white balance, WB, gain of the second camera according to the difference between the RGB-means of the first image data and the RGB-means of the second image data.