Pixel Sampling Using Corner Sample Regions for Anti-Aliasing
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Solution Overview
Problem
Existing graphic processing methods for producing anti-aliased images require high computational power and memory, which is inefficient for devices with limited resources such as portable electronic equipment.
Innovation Solution
A method and apparatus that generate pixel values from sample points positioned within smaller sample regions at the corners of pixels, allowing for reduced computational and memory requirements by sharing sample values between neighboring pixels, with only one sample value needing to be calculated on average for each pixel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If supersampling is used to generate anti-aliased images, then image quality is improved, but computational burden increases significantly
Solution Approach 1:
The patent combines sample points from multiple pixels into shared groups, where a single sample value serves multiple pixels. By organizing sample points in overlapping groups across neighboring pixels and reusing computed sample values, the system reduces redundant calculations while maintaining anti-aliasing quality.
Solution Approach 2:
Each computed sample value serves multiple functions by being shared among multiple pixels. A single sample calculation contributes to the anti-aliasing of several neighboring pixels simultaneously, making the computational resource universally applicable across different pixel locations.
2Device complexity
If multisampling with sample sharing is used, then computational burden is reduced, but memory access requirements increase
Solution Approach 1:
The patent pre-organizes sample points into shared groups before rendering, establishing which sample points will be reused across multiple pixels. This preliminary organization allows the system to compute sample values once and reuse them, avoiding repeated memory accesses during the actual rendering process.
3Quantity of substance
If conventional sampling is used, then memory requirements are low, but anti-aliasing quality is not achieved
Solution Approach 1:
The patent merges sample point calculations across pixel boundaries, creating shared sample groups that provide anti-aliasing information for multiple pixels simultaneously. This merging approach achieves anti-aliasing quality comparable to traditional methods while using fewer total sample values stored in memory.
Data Source
AI summary
A method and a device for generating a pixel value from a plurality of sample values being generated from a plurality of sample points. The method comprises generating a plurality of sample values; and weighting said plurality of sample values for determining said pixel value. Each sample value is generated from one of a plurality of candidate sample points within a sample region. The sample region is positioned at a corner of two intersecting borders of the pixel. The size of the sample region is smaller than the size of the pixel. The device is arranged to carry out the method according to the invention.