Texture synthesis via a noncausal nonparametric multiscale Markov random field

Paget R. and Longstaff I.D. (1998) Texture synthesis via a noncausal nonparametric multiscale Markov random field. IEEE Transactions on Image Processing, 7 6: 925-931. doi:10.1109/83.679446


Author Paget R.
Longstaff I.D.
Title Texture synthesis via a noncausal nonparametric multiscale Markov random field
Journal name IEEE Transactions on Image Processing   Check publisher's open access policy
ISSN 1057-7149
Publication date 1998
Sub-type Article (original research)
DOI 10.1109/83.679446
Volume 7
Issue 6
Start page 925
End page 931
Total pages 7
Subject 1703 Computational Theory and Mathematics
1704 Computer Graphics and Computer-Aided Design
1707 Computer Vision and Pattern Recognition
1712 Software
2208 Electrical and Electronic Engineering
2614 Theoretical Computer Science
Abstract Our noncausal, nonparametric, multiscale, Markov random field (MRF) model is capable of synthesizing 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 realizations of texture visually indistinguishable from the training texture.
Keyword Local annealing
Markov random fields
Multiresolution
Nonparametric estimation
Texture synthesis
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Unknown

Document type: Journal Article
Sub-type: Article (original research)
Collection: Scopus Import
 
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