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IEEE Transactions on Visualization and Computer Graphics

Analytical Texture Mapping

Koen Meinds and Elmar Eisemann

Resampling of warped images has been a topic of research for a long time but only seldomly has focused on theoretically exact resampling. We present a resampling method for minification, applied on the texture mapping function of a 3D graphics pipeline, that is derived from sampling theory without making any approximations. Our method supports freely selectable 2D integratable prefilter (anti-aliasing) functions and uses a 2D box reconstruction filter. We have implemented our method both for CPU and GPU (OpenGL) using multiple prefilter functions defined by piece-wise polynomials. The correctness of our exact resampling method has been made plausible by comparing texture mapping results of our method with those of extreme supersampling. We additionally show how the prefilter of our method can also be applied for high quality polygon edge anti-aliasing. Since our proposed method does not use any approximations, up to numerical precision, it can be used as a reference for approximate texture mapping methods.

More Information

Publisher Paper preprint Appendices of the paper Details of below first video (MPEG4 H.264 encoded) A GPU (OpenGL) Windows implementation of the Analytical Texture Mapping algorithm. For a description and playing instructions see the included atm-GPU-demo-onWindows_README.txt. Playing information of below 2nd, 3rd and 4th (lossless encoded for visual assessment). ATM rendered still pictures. See included atm-still-picture-renderings_README.txt for details.

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Citation

Koen Meinds and Elmar Eisemann, Analytical Texture Mapping, IEEE Transactions on Visualization and Computer Graphics, PP, 2025.

BibTex

@article{bib:meinds:2025,
    author       = { Meinds, Koen and Eisemann, Elmar },    
    title        = { Analytical Texture Mapping },
    journal      = { IEEE Transactions on Visualization and Computer Graphics },
    volume       = { PP },
    year         = { 2025 },
    doi          = { 10.1109/TVCG.2025.3611315 },
    pubmedid     = { 40960976 },
    url          = { https://publications.graphics.tudelft.nl/papers/828 },
}