June 1, 1998

Texture synthesis via a noncausal nonparametric multiscale Markov random field

Key Points

Key points are not available for this paper at this time.

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.

KI fragen

Bookmark

Cite This Study

Paget et al. (Mon,) studied this question.

synapsesocial.com/papers/6a10da96cfa01e990d9fab30 https://doi.org/https://doi.org/10.1109/83.679446

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1A Nonparametric Multiscale Markov Random Field Model For Synthesizing Natural Textures1996 · 9 citations
2Multiple resolution segmentation of textured images1991 · 351 citations
3Textures: A Photographic Album for Artists and Designers1968 · 2,651 citations
4Textons, the elements of texture perception, and their interactions1981 · 1,708 citations
5<title>Novel cluster-based probability model for texture synthesis, classification, and compression</title>1993 · 108 citations

KI fragen

Bookmark