Morphological Anti-Aliasing Method for Boundary Slope Prediction

TL;DR

This paper introduces a morphological anti-aliasing method that predicts boundary slopes to improve line boundary reconstruction and anti-aliasing quality in computer graphics.

Contribution

It proposes a novel global morphological boundary-based approach for more accurate boundary slope prediction and improved anti-aliasing effects with minimal additional computation.

Findings

Enhanced boundary reconstruction accuracy

Improved color transition at boundaries

Higher continuity of inclined straight lines

Abstract

Image pixel aliasing caused by insufficient sampling is a long-standing problem in the field of computer graphics. It has always been the goal of researchers to seek anti-aliasing algorithms with high speed and good effect. Due to the deficiencies in local detection and reconstruction of sloping line boundaries, a morphological anti-aliasing method for boundary slope prediction is proposed. This method uses the information of the local line boundary slope to predict and test the end positions of the line boundary in the global scope, thereby reconstructing The boundary information more consistent with the actual boundary is obtained, and a more accurate linear boundary shape is obtained with only a small increase in the amount of calculation. Compared with the previous morphological anti-aliasing algorithm, the proposed method is based on the global morphological boundary. , can reconstruct the straight line boundary more accurately, and apply it to the anti-aliasing calculation, which can further improve the color transition of the straight line boundary, make the inclined straight line boundary have higher continuity, and obtain a better anti-aliasing effect.