{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T19:08:23Z","timestamp":1783105703863,"version":"3.54.6"},"reference-count":37,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2012,7,1]],"date-time":"2012-07-01T00:00:00Z","timestamp":1341100800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Graph."],"published-print":{"date-parts":[[2012,8,5]]},"abstract":"<jats:p>\n            Procedural noise is a fundamental tool in Computer Graphics. However, designing noise patterns is hard. In this paper, we present\n            <jats:italic>Gabor noise by example<\/jats:italic>\n            , 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.\n          <\/jats:p>","DOI":"10.1145\/2185520.2185569","type":"journal-article","created":{"date-parts":[[2012,8,6]],"date-time":"2012-08-06T18:11:37Z","timestamp":1344276697000},"page":"1-9","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":65,"title":["Gabor noise by example"],"prefix":"10.1145","volume":"31","author":[{"given":"Bruno","family":"Galerne","sequence":"first","affiliation":[{"name":"Universit\u00e9 Paris Descartes and CNRS, Sorbonne Paris Cit\u00e9"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ares","family":"Lagae","sequence":"additional","affiliation":[{"name":"KU Leuven"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sylvain","family":"Lefebvre","sequence":"additional","affiliation":[{"name":"ALICE\/INRIA Nancy Grand-Est"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"George","family":"Drettakis","sequence":"additional","affiliation":[{"name":"REVES\/INRIA Sophia-Antipolis"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2012,7]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1137\/080716542"},{"key":"e_1_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/34.41384"},{"key":"e_1_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1137\/S0895479893259546"},{"key":"e_1_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/1073204.1073264"},{"key":"e_1_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1111\/1467-8659.00149"},{"key":"e_1_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/82.661664"},{"key":"e_1_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/78.229897"},{"key":"e_1_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2052822"},{"key":"e_1_2_2_9_1","volume-title":"-M","author":"Ghazanfarpour D.","year":"1995","unstructured":"Ghazanfarpour , D. , and Dischler , J . -M . 1995 . Spectral analysis for automatic 3-d texture generation. Comp. &amp; Graph . 19, 3, 413--422. Ghazanfarpour, D., and Dischler, J.-M. 1995. Spectral analysis for automatic 3-d texture generation. Comp. &amp; Graph. 19, 3, 413--422."},{"key":"e_1_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1111\/1467-8659.1530311"},{"key":"e_1_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-8659.2010.01738.x"},{"key":"e_1_2_2_12_1","unstructured":"Gilet G. Dischler J.-M. and Soler L. 2010. Procedural descriptions of anisotropic noisy textures by example. In EG 2010 - Short papers 77--80.  Gilet G. Dischler J.-M. and Soler L. 2010. Procedural descriptions of anisotropic noisy textures by example. In EG 2010 - Short papers 77--80."},{"key":"e_1_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/1360612.1360653"},{"key":"e_1_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/218380.218446"},{"key":"e_1_2_2_15_1","doi-asserted-by":"crossref","unstructured":"Hyv\u00e4rinen A. 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Probability Random Variables and Stochastic Processes 4rd ed. McGraw-Hill.  Papoulis A. and Pillai U. 2002. Probability Random Variables and Stochastic Processes 4rd ed. McGraw-Hill."},{"key":"e_1_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/325334.325247"},{"key":"e_1_2_2_31_1","unstructured":"Press W. H. Vetterling W. T. Teukolsky S. A. and Flannery B. P. 2002. Numerical Recipes in C++: the art of scientific computing 2nd ed. Cambridge University Press.   Press W. H. Vetterling W. T. Teukolsky S. A. and Flannery B. P. 2002. Numerical Recipes in C++: the art of scientific computing 2nd ed. Cambridge University Press."},{"key":"e_1_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2007.31"},{"key":"e_1_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/32.92917"},{"key":"e_1_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/355744.355749"},{"key":"e_1_2_2_35_1","unstructured":"Wei L.-Y. Lefebvre S. Kwatra V. and Turk G. 2009. 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