Pixel Weighted Chrominance Correction for Color Bleeding Reduction
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Solution Overview
Problem
Existing methods for reducing color bleeding in digital images, such as those compressed using the discrete cosine transform (DCT), often degrade the definition of object contours while attempting to correct chrominance distortions, as they process images in blocks rather than pixels and rely on imprecise block discrimination.
Innovation Solution
A method that processes digital images by determining chrominance components and assigning weights to pixels within a working window, using fuzzy variables to correct chrominance values without degrading contour definition, by differentiating between pixels based on their proximity to object contours and chrominance gradients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If block-based methods are used to correct color bleeding by averaging chrominance components of surrounding blocks, then color bleeding effects are reduced, but the definition of object contours is worsened
Solution Approach 1:
The patent applies local quality by treating each pixel individually with pixel-specific weights instead of uniform block-based averaging. Pixels closer to object contours receive lower weights to preserve edge sharpness, while pixels in homogeneous regions receive higher weights for effective color bleeding correction. This spatially varying approach allows simultaneous improvement of both color bleeding reduction and contour definition.
Solution Approach 2:
The patent segments the correction process into two distinct stages: first identifying pixels affected by color bleeding through gradient analysis, then applying selective correction only to those pixels while preserving others. This segmentation allows the method to correct color bleeding in affected regions without blurring contours in edge regions, resolving the contradiction between color bleeding reduction and contour definition.
2Productivity
If block discrimination methods are used to identify affected blocks, then correction can be applied selectively, but imprecise discrimination introduces chromatic distortions in blocks originally free of distortion
Solution Approach 1:
The patent segments the image into individual pixels rather than uniform blocks, allowing precise identification of color bleeding affected pixels through gradient analysis. This pixel-level segmentation enables accurate discrimination between affected and unaffected regions, eliminating the chromatic distortions introduced by imprecise block-based discrimination while maintaining correction efficiency.
Solution Approach 2:
The patent replaces the mechanical block-based discrimination system with a gradient-based pixel-level detection system. By calculating chrominance gradients at the pixel level, the method achieves more precise identification of color bleeding effects, substituting the coarse block approach with a finer, more accurate pixel-level mechanism that avoids false positives and chromatic distortions.
3Ease of manufacture
If uniform chrominance correction is applied to all pixels in a block, then implementation is simplified, but pixels differently affected by color bleeding are processed the same way
Solution Approach 1:
The patent implements local quality by computing pixel-specific weights based on each pixel's distance to object contours and its chrominance gradient magnitude. This allows the correction process to adapt to local conditions, applying stronger correction to pixels deeply within homogeneous regions and weaker or no correction to pixels near contours, thereby achieving pixel-specific accuracy while maintaining a unified correction framework.
Solution Approach 2:
The patent introduces dynamics by making the correction strength adaptive rather than fixed. The weight assigned to each pixel dynamically adjusts based on its spatial position relative to contours and its local chrominance characteristics. This dynamic weighting allows the system to simplify implementation through a single formula while achieving pixel-specific precision through automatic adaptation to local image conditions.
Data Source
AI summary
A method of processing digital images to reduce the effects of color bleeding. Chrominance components for pixels in a working window are determined and weights are assigned to the pixels in the working window. A chrominance correction for a center pixel in the working window is generated based on the chrominance components and the assigned weights. Fuzzy variables and thresholds may be applied to generate the assigned weights and the chrominance correction.