Halftone Image Moire Reduction via Gaussian Blur
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Solution Overview
Problem
Moire patterns in halftone images and video content degrade image quality and distract viewers, particularly in downscaled or high-contrast content, where existing technologies fail to effectively eliminate these patterns.
Innovation Solution
A method involving blurring and downscaling of halftone content using a Gaussian blur algorithm, with a user-defined blur radius and scaling factor, to reduce or eliminate moire patterns, while allowing for text removal and reinsertion, and cropping to remove artifacts, thereby enhancing image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If halftone images are downscaled to reduce file size, then storage efficiency improves, but moire patterns appear degrading image quality
Solution Approach 1:
The patent applies a preliminary low-pass filter to the halftone image before downsampling to prevent aliasing artifacts. This pre-processing step removes high-frequency components that would otherwise create moire patterns during the reduction process, thereby maintaining image quality while achieving storage efficiency.
Solution Approach 2:
The patent modifies the frequency domain characteristics of the halftone image by applying spectral filtering techniques. By changing the frequency parameters and removing specific frequency components that cause moire patterns, the system achieves both downsampling and quality preservation.
2Speed
If conventional downscaling methods are used, then processing speed is maintained, but moire patterns are introduced
Solution Approach 1:
The patent extracts and removes the problematic high-frequency components that generate moire patterns from the halftone image before downsampling. By separating and eliminating these harmful frequency components, the system prevents moire pattern formation while maintaining efficient processing speed.
Solution Approach 2:
The patent introduces an intermediary filtering stage between the original halftone image and the downsampling operation. This intermediary low-pass filter acts as a mediator that prepares the image for downsampling by removing aliasing-prone frequencies, thereby preventing moire patterns without significantly impacting processing speed.
3Manufacturing precision
If aggressive filtering is applied to remove moire patterns, then image quality improves, but text and fine details are lost
Solution Approach 1:
The patent applies different filtering strengths to different regions of the image based on local content analysis. Text regions and areas containing fine details receive minimal or no filtering, while regions with halftone patterns receive appropriate low-pass filtering. This localized approach preserves important information while removing moire patterns where they occur.
Solution Approach 2:
The patent employs feedback mechanisms that analyze the image content and dynamically adjust filtering parameters. By monitoring the presence of text and fine details, the system modulates the filtering strength to avoid removing important information while still eliminating moire patterns in appropriate regions.
Data Source
AI summary
Among other disclosed subject matter, a computer-implemented method includes receiving illustrated content. The illustrated content includes half-tone content. The method includes blurring at least part of the illustrated content. The blurring is performed according to a blur radius. The method includes downscaling the blurred illustrated content to an output size.