Morphological Anti-Aliasing Method for Boundary Slope Prediction
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Abstract (arXiv)
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.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Mar 2022.
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Citing papers per year: 2022: 2; 2023: 0; 2024: 1.
3 papers.
- 2024Neural Rendering and Its Hardware Acceleration: A Reviewcited by 4
- 2022Normal and Visibility Estimation of Human Face from a Single Imagecited by 1
- 2022An Interactive Image-based Modeling Systemcited by 1
- 2024Neural Rendering and Its Hardware Acceleration: A Review6 Jan 2024
- 2022An Interactive Image-based Modeling System28 Mar 2022
- 2022Normal and Visibility Estimation of Human Face from a Single Image9 Mar 2022