Publication Details

Low-error Reconstruction of Directional Functions with Spherical Harmonics

VLNAS Michal, MILET Tomáš and ZEMČÍK Pavel. Low-error Reconstruction of Directional Functions with Spherical Harmonics. IEEE Transactions on Visualization and Computer Graphics, vol. 31, no. 10, 2025, pp. 8413-8424. ISSN 1077-2626. Available from: https://ieeexplore.ieee.org/document/11005717
Czech title
Rekonstrukce směrových funkcí s nízkou chybou pomocí sférických harmonických funkcí
Type
journal article
Language
english
Authors
URL
Keywords

spherical harmonics, directional functions, ringing, spherical radial basis functions, visualization, low-error reconstruction, light models

Abstract

This paper proposes a novel approach for the low-error reconstruction of directional functions with spherical harmonics. We introduce a modified version of Spherical Gaussians with adaptive narrowness and amplitude to represent the input data in an intermediate form. This representation is then projected into spherical harmonics using a closed-form analytical solution. Because of the spectral properties of the proposed representation, the amount of ringing artifacts is reduced, and the overall precision of the reconstructed function is improved. The proposed method is more precise comparing to existing methods. The presented solution can be used in several graphical applications, as discussed in this paper. For example, the method is suitable for sparse models such as indirect illumination or reflectance functions.

Published
2025
Pages
8413-8424
Journal
IEEE Transactions on Visualization and Computer Graphics, vol. 31, no. 10, ISSN 1077-2626
Publisher
IEEE Computer Society
DOI
EID Scopus
BibTeX
@ARTICLE{FITPUB13511,
   author = "Michal Vlnas and Tom\'{a}\v{s} Milet and Pavel Zem\v{c}\'{i}k",
   title = "Low-error Reconstruction of Directional Functions with Spherical Harmonics",
   pages = "8413--8424",
   journal = "IEEE Transactions on Visualization and Computer Graphics",
   volume = 31,
   number = 10,
   year = 2025,
   ISSN = "1077-2626",
   doi = "10.1109/TVCG.2025.3570092",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/13511"
}
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