Image Processing Device Dot Dispersion Control
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Solution Overview
Problem
The error diffusion method for image quantization often results in image quality issues such as 'worm' patterns, delayed dot generation, and data distortion, particularly in areas with low dot density, due to mismatched pixel data distribution and propagation errors.
Innovation Solution
An image processing system that generates pixel groups by selecting pixels closest to the center of gravity until the total gradation value reaches a threshold, providing quantized data to the pixel group center, and dynamically updating the reference point for pixel selection to maintain uniform dot dispersion and improve processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If error diffusion method is used for image quantization, then dot dispersion is improved, but worm patterns and data distortion occur
Solution Approach 1:
The image is divided into multiple pixel groups, each processed independently to form separate quantized pixel groups. This segmentation prevents error propagation across the entire image, eliminating the worm pattern effect while maintaining local dot dispersion quality.
Solution Approach 2:
The harmful error diffusion effect is extracted and removed by processing pixel groups independently. Each pixel group's quantization errors are contained within its own group rather than being propagated to subsequent groups, thereby eliminating the chain reaction that causes worm patterns.
2Ease of manufacture
If sequential binarization from left to right is used, then processing simplicity is improved, but dot generation delay occurs in low density areas
Solution Approach 1:
Pixel groups are pre-defined based on center of gravity positions before quantization processing. This preliminary organization allows the system to jump directly to relevant pixel groups for dot generation, avoiding sequential processing delays in low density areas while maintaining processing efficiency.
3Speed
If pixels are selected using predetermined table, then selection speed is improved, but cell distortion and dot clustering occur
Solution Approach 1:
The pixel selection process is made dynamic by continuously updating the center of gravity position based on accumulated pixel data. Instead of using a fixed predetermined table, the system adapts the selection criteria to the actual data distribution, preventing cell distortion while maintaining efficient selection speed through the structured pixel group approach.
Data Source
AI summary
When the image data having a predetermined gradation value for each pixel is input, and the image data is searched from the initial pixel and the total of the gradation values of the pixels, including the searched pixels, becomes a predetermined threshold value or more, a dot is generated at the center of the gravity position as a quantized pixel group. In the searching, an unprocessed pixel closest to the center of gravity position, including this pixel, is selected. If there are a plurality of unprocessed pixels, selection is performed at random. For the pixel selection, a pixel closest to the center position computed from the positional coordinates may be selected, rather than the center of gravity. Also a dot may be generated at the center position of the quantized pixel group.