Image Anti-Aliasing via Hash-Based Grayscale Filtering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Low-resolution graphics and screens cause pixel enlargement, leading to visually distorted edges in computer graphics, which existing anti-aliasing methods fail to adequately address.
Innovation Solution
An image anti-aliasing method and device that generate hash values based on grayscale values and aliasing strength within a selected window, performing filtering to convert aliasing images into smoother anti-aliasing images, utilizing a processing device coupled with a storage device to implement this process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If existing anti-aliasing methods are used, then some aliasing reduction is achieved, but image smoothness and display quality are not sufficiently improved
Solution Approach 1:
The patent changes the parameter of aliasing strength classification by dividing aliasing pixels into multiple categories (first aliasing pixels with lower aliasing strength and second aliasing pixels with higher aliasing strength). This parameter change enables differentiated filtering strategies for different aliasing severity levels, thereby improving image smoothness while maintaining display quality.
Solution Approach 2:
The patent applies local quality by performing anti-aliasing processing differently on different types of pixels. First aliasing pixels and second aliasing pixels are processed with different filtering approaches, and non-aliasing pixels are preserved differently. This localized differentiation improves overall image smoothness without compromising display quality in various regions.
2Reliability
If pixel resolution is increased to reduce aliasing, then display quality improves, but computational complexity and processing requirements increase
Solution Approach 1:
The patent segments the image processing task by first identifying and classifying aliasing pixels into different categories based on aliasing strength. This segmentation allows the system to apply computationally intensive filtering only where necessary (on aliasing pixels) rather than on the entire image, thereby reducing overall processing complexity while maintaining display quality.
Solution Approach 2:
The patent applies partial action by selectively processing only aliasing pixels rather than all pixels in the image. By identifying pixels that actually require anti-aliasing treatment and processing only those, the system reduces computational complexity while still achieving the desired display quality improvement.
Data Source
AI summary
An image anti-aliasing method comprises following steps: receiving an aliasing image; wherein the aliasing image includes a plurality of source pixels; generating a plurality of hash values corresponding to the plurality of source pixels respectively; and performing a filtering processing or a filter generating procedure on the aliasing image according to the plurality of hash values. Each of the plurality of hash values is generated by the following steps: selecting one source pixel from the aliasing image and selecting a window containing the selected source pixel; determining an aliasing strength according to the grayscale values of all the source pixels of a row and a column at which the selected source pixel is located in the window; and determining a hash value of the selected source pixel according to the aliasing strength.