Automatic White Balance Calibration Using Adjusted Golden Set Deviations
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Solution Overview
Problem
Current automatic white balance (AWB) calibration methods fail to accurately calibrate devices with larger manufacturing errors, leading to poor color temperature estimations and reduced imaging quality, as they result in calibration gains that are too large or too small, causing discrepancies between the device's white points and the golden set.
Innovation Solution
The method adjusts the red and blue deviation values of the golden set based on threshold values to minimize differences between the device under calibration and the golden set, ensuring accurate calibration by using adjusted deviation values as golden values, thereby reducing calibration gains and improving consistency across various color temperatures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If current AWB calibration methods are used, then devices with small errors (less than 10%) can be calibrated accurately, but devices with large errors (greater than 15-20%) produce calibration gains that are too large or too small, causing discrepancies between device white points and golden set white points
Solution Approach 1:
The patent divides the calibration process into two stages: first calibrating devices with small errors using conventional methods, then separately calibrating devices with large errors by adjusting the golden set's deviation values. This local differentiation allows each device type to receive appropriate calibration treatment, resolving the contradiction between maintaining accuracy for small-error devices and expanding adaptability to large-error devices.
Solution Approach 2:
The patent changes the parameter values of the golden set's red and blue deviation values specifically for devices with large errors. By adjusting these parameters within predetermined ranges based on the device's actual deviation from the golden set, the calibration process can accommodate large-error devices without producing excessively large or small calibration gains, thus expanding adaptability while maintaining calibration quality.
2Adaptability or versatility
If calibration gains are increased to accommodate devices with large errors, then more devices can be calibrated, but the differences between device white points and golden set white points become too large, reducing calibration quality
Solution Approach 1:
The patent adjusts the golden set's red and blue deviation values as preprocessing parameters before calibration. By setting these parameters within predetermined ranges based on the device's error magnitude, the system can accommodate a broader range of devices (increasing adaptability) while keeping the final calibration gains within acceptable limits (maintaining white point accuracy).
Solution Approach 2:
The patent performs preliminary adjustment of the golden set's deviation values before the actual calibration process. This preliminary action prepares the calibration parameters in advance to match the device's characteristics, ensuring that subsequent calibration operations produce appropriate gains that maintain accuracy while expanding coverage to large-error devices.
3Manufacturing precision
If the golden set's deviation values are adjusted for devices with large errors, then calibration accuracy is maintained, but the calibration process becomes more complex
Solution Approach 1:
The patent applies golden set adjustment only to devices with large errors (greater than 15-20%), while using conventional calibration for devices with small errors (less than 10%). This localized approach maintains calibration accuracy for problematic devices without adding complexity to the entire calibration process, as most devices can still use the simpler conventional method.
Solution Approach 2:
The patent adjusts only specific parameters (red and blue deviation values of the golden set) rather than redesigning the entire calibration process. This targeted parameter adjustment maintains calibration accuracy for large-error devices while minimizing added complexity, as the overall calibration framework remains unchanged and only specific parameter values are modified based on device characteristics.
Data Source
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AI summary
Calibrating automatic white balance by: obtaining (S101) a first white point, acquired by a device under calibration capturing a neutral color under a calibration light source, and a second white point, acquired by a predetermined golden set capturing a neutral color under the calibration light source; if a first difference value between a first and second red deviation values is greater than a first predetermined threshold value and/or a second difference value between a first and second blue deviation values is greater than a second predetermined threshold value, adjusting (S102) the second red deviation value so that the first difference value becomes smaller and/or adjusting the second blue deviation value so that the second difference value becomes smaller; and calibrating (S103) the device using the adjusted second red deviation value and/or the adjusted second blue deviation value as a first golden value and a second golden value, respectively.