Multi-Resolution Sharpness Transport Across Color Channels
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Solution Overview
Problem
Current image sharpening methods, particularly in medical applications, are complex and expensive due to the need for lens data calibration and weighting coefficients, and often result in color contamination, making them unsuitable for real-time applications and inadequate for achieving desired sharpness improvements.
Innovation Solution
A method for improving image sharpness using a novel video signal processing system that calculates weighting coefficients based on multi-resolution sharpness measurement values across multiple levels, allowing for efficient sharpness enhancement without requiring lens data calibration, and operates in color spaces like YUV to maintain color integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional sharpening methods with weighting coefficients are used, then image sharpness is improved, but device complexity and calibration requirements increase
Solution Approach 1:
The patent extracts only the essential sharpness information from color channels by converting to luminance (Y) in YUV color space, discarding color components (U, V) for the sharpening operation. This eliminates the need for complex weighting coefficients while preserving the beneficial sharpness enhancement effect.
Solution Approach 2:
The patent changes the color space parameter from RGB to YUV, allowing separation of luminance and chrominance. By operating only on the luminance component, the system achieves sharpness improvement without needing to determine weighting coefficients for multiple color channels, thus reducing calibration complexity.
2Device complexity
If simple sharpness transport is used, then device complexity is reduced, but color contamination occurs and image quality deteriorates
Solution Approach 1:
The patent segments the image processing into separate luminance and chrominance components in YUV color space. The sharpening operation is applied only to the luminance component, completely separating the sharpness enhancement process from color processing, thus eliminating color contamination while maintaining simple device complexity.
3Measurement precision
If calibration experiments are required, then weighting coefficients can be optimized, but loss of time increases for real-time applications
Solution Approach 1:
The patent extracts only the luminance component for sharpening operations, eliminating the need to determine and store weighting coefficients for multiple color channels. This extraction approach removes the calibration step entirely, enabling real-time processing without time loss.
4Measurement precision
If multiple color channels are processed for sharpness, then image sharpness is improved, but color values are altered and image naturalness decreases
Solution Approach 1:
The patent segments the processing to affect only the luminance component of the YUV color space, leaving the chrominance components (U, V) completely unchanged. This ensures that sharpness is improved while color values remain faithful to the original image, maintaining natural appearance.
Data Source
AI summary
Provided are a system and method for image sharpening is provided that involves capturing an image, and then decomposing the image into a plurality of image-representation components, such as RGB components for example. Each image-representation component is transformed to obtain an unsharpened multi-resolution representation for each image-representation component. A multi-resolution representation includes a plurality of transformation level representations. Sharpness information is transported from an unsharpened transformation level representation of a first one of the image-representation components to a transformation level representation of an unsharpened multi-resolution representation of a second one of the image-representation components to create a sharpened multi-resolution representation of the second one of the image-representation components. The sharpened multi-resolution representation of the second one of the image-representation components is then transformed to obtain a sharpened image. The improved and sharpened image may then be displayed.