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» Modeling Image Textures by Gibbs Random Fields
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106
Voted
ICIP
2006
IEEE
16 years 2 months ago
Spatially Constrained Wiener Filter with Markov Autocorrelation Modeling for Image Resolution Enhancement
This paper develops a practical method for image resolution enhancement. The method optimizes the spatially constrained Wiener filter for an efficiently parameterized model of the...
Jiazheng Shi, Stephen E. Reichenbach
111
Voted
ICIAP
2005
ACM
16 years 22 days ago
3D Functional Models of Monkey Brain Through Elastic Registration of Histological Sections
In this paper we describe a method for the reconstruction and visualization of functional models of monkey brains. Models are built through the registration of high resolution imag...
Fabio Bettio, Francesca Frexia, Andrea Giachetti, ...
117
Voted
CVPR
2008
IEEE
16 years 2 months ago
Visibility in bad weather from a single image
Bad weather, such as fog and haze, can significantly degrade the visibility of a scene. Optically, this is due to the substantial presence of particles in the atmosphere that abso...
Robby T. Tan
ICPR
2004
IEEE
16 years 1 months ago
Unsupervised Image Segmentation Using A Simple MRF Model with A New Implementation Scheme
A Markov random field (MRF) model with a new implementation scheme is proposed for unsupervised image segmentation based on image features. The traditional two-component MRF model...
David A. Clausi, Huawu Deng
VISUALIZATION
1998
IEEE
15 years 4 months ago
Comparing LIC and spot noise
Spot noise and line integral convolution (LIC) are two texture synthesis techniques for vector field visualization. In this paper the two techniques are compared. Continuous direc...
Wim C. de Leeuw, Robert van Liere