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» Trainable Context Model for Multiscale Segmentation
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ICIP
2002
IEEE
14 years 6 months ago
A study of contextual modeling and texture characterization for multiscale Bayesian segmentation
In this paper, we demonstrate that multiscale Bayesian image segmentation can be enhanced by improving both contextual modeling and statistical texture characterization. Firstly, ...
Guoliang Fan, Xiaomu Song
ICNC
2005
Springer
13 years 10 months ago
Texture Segmentation Using Neural Networks and Multi-scale Wavelet Features
This paper presents a novel texture segmentation method using Bayesian estimation and neural networks. Multi-scale wavelet coefficients and the context information extracted from n...
Tae-Hyung Kim, Il Kyu Eom, Yoo Shin Kim
ICIP
2000
IEEE
13 years 9 months ago
Multiscale Texture Segmentation Using Hybrid Contextual Labeling Tree
Wavelet-domain hidden Markov tree (HMT) model has been recently proposed and applied to image processing, e.g., image segmentation. A new multiscale image segmentation method, cal...
Guoliang Fan, Xiang-Gen Xia
EMMCVPR
2007
Springer
13 years 11 months ago
Bayesian Order-Adaptive Clustering for Video Segmentation
Video segmentation requires the partitioning of a series of images into groups that are both spatially coherent and smooth along the time axis. We formulate segmentation as a Bayes...
Peter Orbanz, Samuel Braendle, Joachim M. Buhmann