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Texture synthesis by non-parametric sampling

Efros, A.A., Leung, T.K.·1999·Proceedings of the Seventh IEEE International Conference on Computer Vision

Abstract

A non-parametric method for texture synthesis is proposed. The texture synthesis process grows a new image outward from an initial seed, one pixel at a time. A Markov random field model is assumed, and the conditional distribution of a pixel given all its neighbors synthesized so far is estimated by querying the sample image and finding all similar neighborhoods. The degree of randomness is controlled by a single perceptually intuitive parameter. The method aims at preserving as much local structure as possible and produces good results for a wide variety of synthetic and real-world textures.

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Research works printed but not linked: 12

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  8. popat, 1993, Novel cluster-based probability model for texture synthesis, classification, and compression, Proc SPIE Visual Comm and Image Processing, 10.1117/12.157992 · DOI
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  11. portilla, 1999, Texture representation and synthesis using correlation of complex wavelet coefficient magnitudes
  12. 10.1145/258734.258882 · DOI · Paper page

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Metadata

Authors
Efros, A. A., & Leung, T. K.
Venue
Proceedings of the Seventh IEEE International Conference on Computer Vision
Publisher
IEEE
Published
1999
Pages
1033-1038 vol.2
OpenAlex
W2116013899
Cited by
3,023
References
1
FWCI
17.71
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Texture synthesis by non-parametric sampling. https://app.cochat.ai/papers/10.1109/iccv.1999.790383
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Efros, A. A., & Leung, T. K. (1999). Texture synthesis by non-parametric sampling. Proceedings of the Seventh IEEE International Conference on Computer Vision. https://doi.org/10.1109/iccv.1999.790383

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