Auto Color Correction Module for Image Sensors
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Solution Overview
Problem
Electronic devices with digital camera modules face challenges in adjusting captured images to match the original colors observed by the human eye, due to varying environment parameters and limitations in image sensor and lens brightness, which affects color accuracy and brightness uniformity.
Innovation Solution
An auto-color-correction method and module that calculates color temperatures of pixels, generates correction parameters based on pixel distributions in different color temperature ranges, and adapts chrominance and lens shading correction parameters to optimize image compensation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If color correction is performed using fixed parameters, then the correction process is simple and fast, but the color accuracy deteriorates under different environmental lighting conditions
Solution Approach 1:
The patent applies dynamics by transitioning from fixed correction parameters to dynamic parameters that automatically adapt to different lighting conditions. The system calculates color temperature weights based on pixel color temperature distributions and uses these weights to generate correction parameters that vary with environmental conditions, enabling the color correction to dynamically adjust and maintain accuracy across different scenarios
Solution Approach 2:
The patent implements parameter changes by modifying correction parameters based on calculated color temperature weights. Different color temperature ranges correspond to different correction parameters, and the system seamlessly switches between these parameters according to the dominant color temperature in the image, thereby improving color accuracy without requiring manual intervention
2Measurement precision
If chrominance correction is applied to correct color temperature, then color accuracy improves, but brightness uniformity deteriorates due to lens shading effects
Solution Approach 1:
The patent applies segmentation by dividing the correction process into independent chrominance correction and brightness correction components. The chrominance correction handles color temperature variations, while the brightness correction (lens shading correction) independently addresses brightness uniformity issues. This segmentation allows each correction type to optimize its function without interfering with the other
Solution Approach 2:
The patent implements local quality by applying different correction strategies to different regions of the image. Lens shading correction is applied to correct brightness variations in specific regions (typically peripheral areas), while chrominance correction is applied globally to adjust color temperature. This localized approach ensures that each region receives the appropriate correction without compromising overall brightness uniformity
3Stability of the object's composition
If lens shading correction is performed to improve brightness uniformity, then brightness distribution improves, but color accuracy deteriorates due to over-correction in certain regions
Solution Approach 1:
The patent applies segmentation by separating brightness correction and color correction into independent operations. Lens shading correction handles brightness uniformity independently, while chrominance correction independently handles color accuracy. This segmentation prevents the over-correction problem that occurs when corrections are applied sequentially without independence
Solution Approach 2:
The patent implements parameter changes by using different correction parameters for different regions and correction types. The system calculates region-specific correction parameters for lens shading correction while maintaining separate color temperature correction parameters. This independent parameter adjustment allows brightness and color corrections to be optimized simultaneously without mutual interference
Data Source
AI summary
An auto-color-correction method for an image capturing device includes calculating a plurality color temperatures of a plurality of pixels in an image; calculating a number of pixels of the plurality of pixels located in a first color temperature range as a first number and a number of pixels of the plurality of pixels located in a second color temperature range as a second number; generating a color temperature weight according to the first number and the second number; and generating at least one correction coefficient according to the color temperature weight, at least one first coefficient corresponding to the first color temperature range and at least one second coefficient corresponding to the second color temperature range.