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Texture synthesis via a noncausal nonparametric multiscale markov random field (1997).
| Content Provider | CiteSeerX |
|---|---|
| Author | Paget, Rupert Longstaff, I. D. |
| Abstract | Our noncausal, nonparametric, multiscale, Markov random field (MRF) model is capable of synthesising and capturing the characteristics of a wide variety of textures, from the highly structured to the stochastic. We use a multiscale synthesis algorithm incorporating local annealing to obtain larger realisations of texture visually indistinguishable from the training texture. 4 Keywords Markov random fields, Nonparametric estimation, Texture synthesis, Multi-resolution, Local annealing. 1 The authors are affiliated with the Department of Electrical and Computer Engineering, University of Queensland and the Cooperative Research Centre for Sensor, Signal, and Information Processing. 2 Rupert Paget is at the Department of Electrical and Computer Engineering, University of Queensland, QLD 4072 AUSTRALIA, Tel: (+61) 7 365 3697, Fax: (+61) 7 365 3684, email: paget@elec.uq.edu.au 3 Dennis Longstaff is at the Department of Electrical and Computer Engineering, University of Queensland, QLD... |
| File Format | |
| Publisher Date | 1997-01-01 |
| Access Restriction | Open |
| Subject Keyword | Texture Synthesis Computer Engineering Nonparametric Estimation Markov Random Field Dennis Longstaff Paget Elec Information Processing Wide Variety Cooperative Research Centre Multiscale Synthesis Algorithm Keywords Markov Random Field Training Texture |
| Content Type | Text |
