Halftone Image Processing with Moire Suppression and Contrast Enhancement
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Solution Overview
Problem
Existing halftone processing techniques, such as those using threshold value matrices, often result in reduced image quality due to loss of high-frequency components, particularly at image edges, leading to reduced contrast and unclear print results.
Innovation Solution
An image processing device that performs quantization processing using a threshold value matrix, with a derivation unit, determination units, and a correction unit to adjust pixel values based on reference areas and threshold values, ensuring accurate dot placement and pattern reproduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If dither processing using a threshold value matrix is applied to convert a digital image to a halftone image, then the number of tones is reduced to match printer output capabilities, but high-frequency components are lost resulting in reduced contrast and unclear image edges
Solution Approach 1:
The patent segments the image processing into multiple stages: first performing conventional dither processing to reduce tones, then separately detecting and processing moire components through filter processing. This segmentation allows the system to handle tone reduction and high-frequency preservation as distinct operations, preventing the loss of image quality that occurs in conventional single-stage processing.
Solution Approach 2:
The patent extracts the moire component from the halftone image through bandpass filter processing. By separating and identifying the moire component specifically, the system can then perform weighted averaging to preserve these high-frequency components while maintaining the tone-reduced halftone effect, thus preventing contrast loss and edge blurring.
2Productivity
If conventional dither processing is used to match printer output tones, then the processing is simple and fast, but moire patterns and interference occur reducing image quality
Solution Approach 1:
The patent introduces an intermediary processing stage between conventional dither processing and final output. The moire component detection and filter processing act as an intermediary that identifies and handles problematic moire patterns separately, allowing the system to maintain fast processing speeds while eliminating the harmful moire effect through targeted intervention rather than complete reprocessing.
Solution Approach 2:
The patent implements feedback by detecting the moire component in the halftone image and using this information to adjust the final output through weighted averaging. The system feeds back the detected moire characteristics to modify the processing result, enabling automatic suppression of moire patterns while preserving image quality without requiring manual intervention or slow iterative processing.
Data Source
AI summary
A quantized value for a pixel of interest in an input image is derived by using a predetermined threshold value matrix. Then, based on a pixel value group in a predetermined reference area including the pixel of interest in the input image and a threshold value group corresponding thereto, directionality of correction is determined. Further, based on the pixel value group and the threshold value group, whether or not the pixel of interest satisfies a predetermined condition for changing the quantized value is determined. Then, based on both the determination results, the quantized value is corrected.