Image Signal Processor White Balance for Region-Specific Color Shading
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Solution Overview
Problem
Existing white balance processing techniques in imaging devices are sub-optimal when applied to pixel arrays where multiple pixels share a single micro lens or when micro lenses vary in curvature and height, leading to unbalanced color reproduction.
Innovation Solution
Adaptive white balance correction is performed by calculating region-specific white balance gains based on region-specific color shading weights and global white balance gains, allowing for independent correction of image regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If global white balance processing is applied uniformly across the entire image, then processing simplicity is maintained, but color uniformity across different regions deteriorates due to micro lens variations
Solution Approach 1:
The image is divided into multiple regions (e.g., first region and second region) with different micro lens characteristics. Each region is processed independently with its own white balance parameters, allowing region-specific color correction while maintaining overall system manageability.
Solution Approach 2:
Different white balance parameters (first white balance parameters for the first region, second white balance parameters for the second region) are applied to different regions of the image. This ensures that each region receives optimized color correction tailored to its specific micro lens characteristics, improving overall color uniformity.
2Manufacturing precision
If region-specific white balance processing is implemented, then color uniformity is improved, but processing complexity increases
Solution Approach 1:
Region division and the determination of region-specific white balance parameters are performed in advance during image processing setup. This preliminary preparation allows the actual white balance correction to be applied efficiently without adding significant complexity to the real-time processing stage.
Solution Approach 2:
The system dynamically selects and applies different white balance parameters based on the specific region being processed. The image processing device adapts its processing approach according to the micro lens characteristics of each region, optimizing color correction while managing complexity through structured region-based processing.
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
Ensures balanced color reproduction across different regions of an image by applying adaptive white balance gains, addressing non-uniformity caused by shared micro lenses and varying lens curvatures.
Implementation Method 1
The light-sensing element may generate an electrical signal depending on the intensity of light absorbed by the light-sensing element
Data Source
AI summary
A method of operating an image signal processor includes storing, by a color shading profile storage circuit, region-specific color shading values extracted from first image data, obtaining, by a region of interest-obtaining circuit, a region of interest, receiving, by a global white balance gain-receiving circuit, a global white balance gain from an application processor, calculating, by a region-specific white balance gain-calculating circuit, region-specific color shading weights, based on a first color shading value of the region of interest and a second color shading value for each region, calculating, by the region-specific white balance gain-calculating circuit, region-specific white balance gains, based on the global white balance gain and the region-specific color shading weights, and correcting, by a white balance-correcting circuit, white balance of second image data, based on the region-specific white balance gains.