期刊
ACM TRANSACTIONS ON GRAPHICS
卷 31, 期 4, 页码 -出版社
ASSOC COMPUTING MACHINERY
DOI: 10.1145/2185520.2185569
关键词
procedural noise; Gaussian texture; Gaussian random field; power spectrum estimation; non-negative basis pursuit denoising; decorrelated color space
资金
- ANR project MATAIM [ANR-09-BLAN-0029-01]
- KU Leuven project [CREA/08/017]
- ANR project SIMILAR-CITIES [2008-COORD-021-01]
- EU project VERVE
- NVIDIA (Academic Partnership Program)
- Agence Nationale de la Recherche (ANR) [ANR-09-BLAN-0029] Funding Source: Agence Nationale de la Recherche (ANR)
Procedural noise is a fundamental tool in Computer Graphics. However, designing noise patterns is hard. In this paper, we present Gabor noise by example, a method to estimate the parameters of bandwidth-quantized Gabor noise, a procedural noise function that can generate noise with an arbitrary power spectrum, from exemplar Gaussian textures, a class of textures that is completely characterized by their power spectrum. More specifically, we introduce (i) bandwidth-quantized Gabor noise, a generalization of Gabor noise to arbitrary power spectra that enables robust parameter estimation and efficient procedural evaluation; (ii) a robust parameter estimation technique for quantized-bandwidth Gabor noise, that automatically decomposes the noisy power spectrum estimate of an exemplar into a sparse sum of Gaussians using non-negative basis pursuit denoising; and (iii) an efficient procedural evaluation scheme for bandwidth-quantized Gabor noise, that uses multi-grid evaluation and importance sampling of the kernel parameters. Gabor noise by example preserves the traditional advantages of procedural noise, including a compact representation and a fast on-the-fly evaluation, and is mathematically well-founded.
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