Adaptive Image Sharpness Control for Skin Noise Reduction
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Solution Overview
Problem
Digital images often suffer from noise and ringing effects due to oversharpening, especially in human skin areas and low light exposures, which are not effectively addressed by existing image enhancement methods.
Innovation Solution
An adaptive image improvement system comprising an image analyzer, human skin processing unit, noise reducer, and visual resolution enhancer that detects human skin, reduces saturation and sharpness of skin areas, and adjusts high-frequency components to minimize noise and ringing, while enhancing texture and brightness for improved visual quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If image sharpness is enhanced by increasing high frequency components, then image sharpness is improved, but noise and ringing effects increase
Solution Approach 1:
The patent applies different processing strengths to different regions of the image. The adaptive processor calculates a processing strength value for each pixel based on local characteristics such as edge presence, noise levels, and texture complexity. This allows sharpness enhancement to be applied selectively - stronger enhancement in regions that benefit from it while avoiding or reducing enhancement in regions prone to noise and ringing artifacts.
Solution Approach 2:
The processing strength is dynamically adjusted for each pixel rather than applying a uniform enhancement across the entire image. The system adaptively determines the optimal processing strength based on local image characteristics, making the enhancement dynamic and context-dependent. This dynamic approach prevents over-enhancement in sensitive areas while maintaining sharpness where needed.
2Manufacturing precision
If uniform sharpness enhancement is applied to the entire image, then overall sharpness is improved, but skin areas and low light regions suffer from over-enhancement and incorrect sharpness changes
Solution Approach 1:
The patent transitions from uniform global enhancement to localized adaptive enhancement. Each pixel's processing strength is independently determined based on its local characteristics including whether it belongs to skin regions, low light areas, or contains natural edges. This local quality approach ensures that sharpness enhancement is context-appropriate and avoids the incorrect changes that occur with uniform enhancement.
Solution Approach 2:
The system changes the processing parameter (processing strength) based on the local characteristics of each pixel. By analyzing features such as luminance, chrominance, edge orientation, and texture, the system dynamically adjusts the enhancement parameter to match the local requirements, thereby achieving correct sharpness enhancement across diverse image regions.
Data Source
AI summary
A method includes improving an input image generally to compensate for the differences between how an image sensor views an object and how the human visual system views the object and generating a printout of the improved image at a faster print speed than that which would generate a printout of the input image. The improved image printout has at least the same or better visual quality than the input image printout. Improving the image includes analyzing an input image, reducing saturation levels for areas of human skin under low light exposures and improving the visual resolution of the input image.