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» Trainable Context Model for Multiscale Segmentation
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38
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ICIP
1998
IEEE
16 years 14 days ago
Trainable Context Model for Multiscale Segmentation
Hui Cheng, Charles A. Bouman
ICIP
2002
IEEE
16 years 16 days 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
77
Voted
ICNC
2005
Springer
15 years 4 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
15 years 3 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
85
Voted
EMMCVPR
2007
Springer
15 years 5 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