Anti-aliasing Image Processing Using Edge Binarization and Template Matching
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Solution Overview
Problem
Conventional image processing techniques for anti-aliasing require significant computational resources due to the need for extensive edge detection calculations across pixel blocks, leading to a heavy processing load.
Innovation Solution
An image processing apparatus and method that sets a viewing window to determine differences between adjacent pixel values, using a weighted addition of pixel values based on combination determination information to reduce the number of calculations required for anti-aliasing, with stored determination results reused to minimize data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional edge detection operators (Sobel or Laplacian) are used to calculate edge information for anti-aliasing, then edge detection accuracy is improved, but processing load increases significantly
Solution Approach 1:
The patent segments the image processing into distinct stages: edge detection using simple difference calculation, binarization of edge information, template matching for jaggy detection, and anti-aliasing processing. This segmentation allows each stage to use optimized methods, with edge detection using computationally simple operations that can be efficiently parallelized.
Solution Approach 2:
The patent performs preliminary binarization of edge information before template matching. By converting edge intensity values to binary edge/non-edge information in advance, the subsequent template matching operation becomes simpler and faster, reducing the overall processing load while maintaining detection accuracy.
2Measurement precision
If pattern matching is performed on multi-level image data directly, then jaggy detection accuracy is improved, but circuit size and processing cost increase
Solution Approach 1:
The patent transforms the parameter representation of image data by binarizing edge information before pattern matching. This parameter change converts multi-level intensity data into binary edge/non-edge data, which simplifies the pattern matching logic and reduces circuit complexity while maintaining jaggy detection accuracy through subsequent template-based analysis.
3Loss of information
If edge detection is performed for every pixel in a pixel block, then comprehensive edge information is obtained, but calculation processing time increases
Solution Approach 1:
The patent merges the edge detection operation with the anti-aliasing processing by using the same pixel difference calculations for both purposes. The difference calculations performed for edge detection are reused to determine anti-aliasing application, eliminating redundant computations and reducing overall processing time while maintaining complete edge information coverage.
Data Source
AI summary
An image processing apparatus and method is provided which performs anti-aliasing on input image data. The apparatus and method may be utilized to improve resolution of, for example, images formed by a group of dots and lines, such as characters and marks. The apparatus and method disclosed herein can perform anti-aliasing with a lighter processing load than previously disclosed methods.