Guided Image Filter Radius Adaptation for Chrominance Upsampling
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Solution Overview
Problem
Visual artifacts occur when up-sampling image data from a lower quality color space to a higher quality color space, reducing the quality of the presented content.
Innovation Solution
A method and system that up-sample the chrominance component of image data using a guided image filter, where the radius parameter of the filter is variable and determined based on analysis of the luminance component to minimize artifacts, allowing for adaptive filtering across different pixels or regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If up-sampling is performed to convert from lower quality color space to higher quality color space, then the color space quality is improved, but visual artifacts occur reducing the presented content quality
Solution Approach 1:
The patent applies local quality by using a guided image filter with spatially varying radius parameters. The filter adapts its smoothing strength locally based on the luminance guide image, applying stronger filtering in homogeneous regions and weaker filtering near edges. This allows the up-sampling to achieve high color space quality while minimizing visual artifacts through localized adaptive processing.
Solution Approach 2:
The patent changes the radius parameter of the guided image filter dynamically based on the analysis of the luminance component. By varying the radius parameter across different regions of the image, the system optimizes the balance between smoothing artifacts and preserving detail, thereby improving color space conversion quality while reducing harmful visual artifacts.
2Device complexity
If a fixed radius parameter is used for the guided image filter, then the filtering process is simple, but the filtering quality varies across different image regions
Solution Approach 1:
The patent implements dynamics by transitioning from a fixed radius parameter to a dynamic, spatially varying radius parameter. The radius is determined by analyzing the luminance component and adjusting the filter strength adaptively for different regions. This dynamic approach maintains relatively simple filtering operations while significantly improving filtering quality consistency across diverse image regions.
3Manufacturing precision
If the radius parameter is made variable for different pixels or regions, then the filtering quality is improved, but the computational complexity increases
Solution Approach 1:
The patent applies preliminary action by first analyzing the luminance component to determine the radius parameter map before performing the actual chrominance up-sampling and filtering. This pre-computation of the guide image and radius parameters allows the subsequent filtering to proceed efficiently with adaptive quality, reducing the computational burden during the main processing stage while maintaining high filtering quality.
Data Source
AI summary
Apparatus 10 for processing image data comprises an input 11 arranged to receive image data representing an image. The image data comprises a luminance component 13 at a first spatial resolution and at least one chrominance component 14 at a second, lower, spatial resolution. An up-sampling unit 18 up-samples the spatial resolution of the at least one chrominance component 14 to form an up-sampled chrominance component. A guided image filter (GIF) 20 filters the up-sampled chrominance component. The guided image filter comprises a radius parameter which determines an extent of the filter around a pixel. A control unit 15 for the guided image filter 20 determines a value of the radius parameter of the guided image filter. The value of the radius parameter is variable for different pixels of the image, or for different regions of pixels of the image. The control unit 15 can analyze the image data to determine the value of the radius parameter.