Aperture-Driven Color Kill for False Color Artifact Reduction
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Solution Overview
Problem
Existing image processing technologies face challenges in reducing false color artifacts, particularly along black-to-white transitions, without requiring additional or higher-quality hardware, which is impractical for low-cost imagers.
Innovation Solution
A method and apparatus that determine an aperture correction value based on brightness transitions, calculate an attenuation value using color saturation and gain settings, and adjust color saturation of pixels to reduce false color artifacts, specifically by operating within an image processor associated with a pixel array or as a separate processor receiving captured image data, utilizing a system that processes pixels in the YUV color space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If additional hardware components or higher-quality hardware components are used to correct false color artifacts, then image quality is improved, but device cost and complexity increase
Solution Approach 1:
The patent replaces hardware-based solutions (additional lenses, higher-quality pixel arrays) with a software-based image processing algorithm. The system detects false color artifacts through aperture-driven color kill analysis and corrects them through mathematical calculations involving attenuation values and color saturation adjustments, eliminating the need for physical hardware modifications.
Solution Approach 2:
The patent modifies image parameters (color saturation values, attenuation factors) to correct false color artifacts. By calculating aperture correction values and adjusting color saturation based on brightness transitions and chrominance analysis, the system achieves image quality improvement through parameter manipulation rather than hardware changes.
2Object-generated harmful factors
If color saturation is reduced to eliminate false color artifacts, then artifact reduction is achieved, but desirable coloration is lost
Solution Approach 1:
The patent applies different color saturation adjustment strategies to different regions of the image based on local characteristics. By analyzing brightness transitions and aperture values at specific pixel locations, the system selectively attenuates color saturation only where false color artifacts are detected, while preserving color fidelity in regions where natural coloration is present.
Solution Approach 2:
The system uses feedback from chrominance analysis and brightness transition detection to dynamically adjust color saturation. The aperture correction value is calculated based on detected brightness transitions, and this feedback is used to determine the appropriate attenuation factor, ensuring that color saturation is reduced only when and where artifacts are present.
3Object-generated harmful factors
If aperture correction is applied to reduce false color artifacts, then artifact reduction is achieved, but processing complexity increases
Solution Approach 1:
The patent divides the image processing task into discrete, manageable segments: detecting brightness transitions, calculating aperture correction values, determining attenuation factors, and adjusting color saturation. This segmentation allows the complex artifact correction process to be implemented through a series of simple, sequential operations rather than a single complex algorithm.
Data Source
AI summary
A method and apparatus for reducing false color artifacts in digital images. Aperture correction and color saturation values are determined for a portion of an image surrounding a subject pixel. A color attenuation value is determined based at least in part on the aperture correction and color saturation values. A color value of the subject pixel is adjusted by an amount based at least in part on the color attenuation value. In one exemplary embodiment, the method and apparatus operate in the YUV color space and adjust U and V values of the subject pixel proportionally to the color attenuation value.