Electronic Camera Auto White Balance Self-Training Calibration
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Solution Overview
Problem
Existing electronic cameras face challenges in achieving accurate auto white balancing due to sensor variations and the high cost of individual calibration, often relying on a golden module calibration that may not account for unique spectral properties of each sensor, leading to color cast errors.
Innovation Solution
An automated self-training method that allows electronic cameras to calibrate auto white balance parameters by capturing images of real-life scenes under various illuminants, using a base parameter set from a golden module and refining it through user-driven imaging to produce camera-specific fully calibrated parameters, reducing manufacturer costs and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If golden module calibration is used to reduce manufacturing costs, then manufacturing cost decreases, but white balance accuracy deteriorates due to sensor variations
Solution Approach 1:
The camera performs self-calibration by automatically capturing images of real-life scenes and using scene analysis algorithms to determine white balance parameters, eliminating the need for expensive manual calibration of each sensor while achieving sensor-specific accuracy
Solution Approach 2:
The system changes calibration parameters dynamically by adapting white balance settings based on actual scene content and lighting conditions captured by the specific sensor, rather than using fixed golden module parameters, thereby achieving both cost reduction and accuracy
2Measurement precision
If sensor-by-sensor calibration is performed to improve white balance accuracy, then white balance accuracy improves, but manufacturing cost increases
Solution Approach 1:
Each sensor automatically calibrates itself by analyzing real-life scenes it captures, eliminating the need for expensive factory calibration equipment and manual procedures while achieving sensor-specific accuracy
Solution Approach 2:
The system creates a digital model of the specific sensor's spectral characteristics by analyzing captured images, then uses this copied sensor profile to optimize white balance parameters without requiring physical calibration hardware
3Measurement precision
If automated self-training is implemented to achieve camera-specific calibration, then white balance accuracy improves, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical calibration equipment with software-based scene analysis algorithms that automatically determine white balance parameters from captured images, reducing hardware complexity while maintaining accuracy
Data Source
AI summary
A method for calibrating auto white balancing in an electronic camera includes (a) obtaining a plurality of color values from a respective plurality of images of real-life scenes captured by the electronic camera under a first illuminant, (b) invoking an assumption about a true color value of at least portions of the real-life scenes, and (c) determining, based upon the difference between the true color value and the average of the color values, a plurality of final auto white balance parameters for a respective plurality of illuminants including the first illuminant. An electronic camera device includes an image sensor for capturing real-life images of real-life scenes, instructions including a partly calibrated auto white balance parameter set and auto white balance self-training instructions, and a processor for processing the real-life images according to the self-training instructions to produce a fully calibrated auto white balance parameter set specific to the electronic camera.