@InProceedings{6952617,
  author = {B. Galerne and A. Leclaire and L. Moisan},
  booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)},
  title = {A texton for fast and flexible Gaussian texture synthesis},
  year = {2014},
  pages = {1686-1690},
  abstract = {Gaussian textures can be easily simulated by convolving an image sample with a white noise. However, this procedure is not very flexible (it does not allow for non-uniform grids in particular), and becomes computationally heavy for very large domains. We here propose an algorithm that summarizes a texture sample into a synthesis-oriented texton, that is, a small image for which the discrete spot noise simulation (summed and normalized randomly-shifted copies of the texton) is more efficient than the classical convolution algorithm. Using this synthesis-oriented texture summary, Gaussian textures can be generated on-demand in a faster, simpler, and more flexible way.},
  keywords = {convolution;Gaussian processes;image texture;white noise;classical convolution algorithm;normalized randomly-shifted texton copy;discrete spot noise simulation;synthesis-oriented texton;white noise;flexible Gaussian texture synthesis;fast Gaussian texture synthesis;Computational modeling;Noise;Kernel;Approximation methods;Approximation algorithms;Convolution;Convergence;Spot noise;texton;Gaussian texture;texture synthesis;error reduction algorithm},
  issn = {2076-1465},
  month = {Sep.},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569925559.pdf},
}

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We here propose an algorithm that summarizes a texture sample into a synthesis-oriented texton, that is, a small image for which the discrete spot noise simulation (summed and normalized randomly-shifted copies of the texton) is more efficient than the classical convolution algorithm. Using this synthesis-oriented texture summary, Gaussian textures can be generated on-demand in a faster, simpler, and more flexible way.","keywords":"convolution;Gaussian processes;image texture;white noise;classical convolution algorithm;normalized randomly-shifted texton copy;discrete spot noise simulation;synthesis-oriented texton;white noise;flexible Gaussian texture synthesis;fast Gaussian texture synthesis;Computational modeling;Noise;Kernel;Approximation methods;Approximation algorithms;Convolution;Convergence;Spot noise;texton;Gaussian texture;texture synthesis;error reduction algorithm","issn":"2076-1465","month":"Sep.","url":"https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569925559.pdf","bibtex":"@InProceedings{6952617,\n author = {B. Galerne and A. Leclaire and L. Moisan},\n booktitle = {2014 22nd European Signal Processing Conference (EUSIPCO)},\n title = {A texton for fast and flexible Gaussian texture synthesis},\n year = {2014},\n pages = {1686-1690},\n abstract = {Gaussian textures can be easily simulated by convolving an image sample with a white noise. However, this procedure is not very flexible (it does not allow for non-uniform grids in particular), and becomes computationally heavy for very large domains. We here propose an algorithm that summarizes a texture sample into a synthesis-oriented texton, that is, a small image for which the discrete spot noise simulation (summed and normalized randomly-shifted copies of the texton) is more efficient than the classical convolution algorithm. Using this synthesis-oriented texture summary, Gaussian textures can be generated on-demand in a faster, simpler, and more flexible way.},\n keywords = {convolution;Gaussian processes;image texture;white noise;classical convolution algorithm;normalized randomly-shifted texton copy;discrete spot noise simulation;synthesis-oriented texton;white noise;flexible Gaussian texture synthesis;fast Gaussian texture synthesis;Computational modeling;Noise;Kernel;Approximation methods;Approximation algorithms;Convolution;Convergence;Spot noise;texton;Gaussian texture;texture synthesis;error reduction algorithm},\n issn = {2076-1465},\n month = {Sep.},\n url = {https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569925559.pdf},\n}\n\n","author_short":["Galerne, B.","Leclaire, A.","Moisan, L."],"key":"6952617","id":"6952617","bibbaseid":"galerne-leclaire-moisan-atextonforfastandflexiblegaussiantexturesynthesis-2014","role":"author","urls":{"Paper":"https://www.eurasip.org/proceedings/eusipco/eusipco2014/html/papers/1569925559.pdf"},"keyword":["convolution;Gaussian processes;image texture;white noise;classical convolution algorithm;normalized randomly-shifted texton copy;discrete spot noise simulation;synthesis-oriented texton;white noise;flexible Gaussian texture synthesis;fast Gaussian texture synthesis;Computational modeling;Noise;Kernel;Approximation methods;Approximation algorithms;Convolution;Convergence;Spot noise;texton;Gaussian texture;texture synthesis;error reduction algorithm"],"metadata":{"authorlinks":{}},"downloads":0},"bibtype":"inproceedings","biburl":"https://raw.githubusercontent.com/Roznn/EUSIPCO/main/eusipco2014url.bib","creationDate":"2021-02-13T17:43:41.723Z","downloads":0,"keywords":["convolution;gaussian processes;image texture;white noise;classical convolution algorithm;normalized randomly-shifted texton copy;discrete spot noise simulation;synthesis-oriented texton;white noise;flexible gaussian texture synthesis;fast gaussian texture synthesis;computational modeling;noise;kernel;approximation methods;approximation algorithms;convolution;convergence;spot noise;texton;gaussian texture;texture synthesis;error reduction algorithm"],"search_terms":["texton","fast","flexible","gaussian","texture","synthesis","galerne","leclaire","moisan"],"title":"A texton for fast and flexible Gaussian texture synthesis","year":2014,"dataSources":["A2ezyFL6GG6na7bbs","oZFG3eQZPXnykPgnE"]}