477 search results - page 14 / 96 » Modeling Image Textures by Gibbs Random Fields |
91
Voted
ICIP
2009
IEEE
15 years 9 months ago
2009
IEEE
We propose a binary Markov Random Field (MRF) model
that assigns high probability to regions in the image domain
consisting of an unknown number of circles of a given radius.
We...
99
Voted
SIBGRAPI
1999
IEEE
15 years 2 months ago
1999
IEEE
Texture analysis and synthesis is very important for computer graphics, vision, and image processing. This paper describes an algorithm which can produce new textures with a matchi...
91
Voted
CVPR
2010
IEEE
15 years 6 months ago
2010
IEEE
Markov random fields (MRFs) are popular and generic probabilistic models of prior knowledge in low-level vision. Yet their generative properties are rarely examined, while applica...
111
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ICPR
2008
IEEE
15 years 11 months ago
2008
IEEE
Usually changes in remote sensing images go along with the appearance or disappearance of some edges. In addition, pixels located along the edges are likely to weakly influenced b...
ECCV
2006
Springer
16 years 2 days ago
2006
Springer
We present a dynamic near-regular texture (NRT) tracking algorithm nested in a lattice-based Markov-Random-Field (MRF) model of a 3D spatiotemporal space. One basic observation use...