Bea2011b

[Bea2011b]
Mean-Shift Clustering and Hierarchical Segmentation for Polsar Image Analysis

Authors:Beaulieu Jean-Marie, Ridha Touzi

Conference:Advanced SAR Workshop 2011, Canadian Space Agency

 Montreal (Saint-Hubert)

 June 2011, p. 6

URL:http://www.asc-csa.gc.ca

Abstract:   Image segmentation and unsupervised classification are difficult problems. We propose to combine both. A clustering process is applied over segment mean values. Only large segments are considered. The clustering is composed of a mean-shift step and a hierarchical clustering step. The hierarchical grouping is based upon a powerful segmentation technique previously developed [1]. The approach is applied on a 9-look polarimetric SAR image. Textured and non- textured image regions are considered. The K and Wishart distributions are used respectively. The unsupervised classification results can be very useful for image analysis and further supervised classification. The obtained region groups constitute an important simplification of the image.

Mean-Shift Clustering and Hierarchical Segmentation for Polsar Image Analysis,
Beaulieu Jean-Marie, Ridha Touzi,
Advanced SAR Workshop 2011, Canadian Space Agency, Montreal (Saint-Hubert), June 2011, p. 6.
[Bibtex]

@Conference{Bea2011b,
author = {Beaulieu, Jean-Marie and Touzi, Ridha},
editor = {},
title = {Mean-Shift Clustering and Hierarchical Segmentation for Polsar Image Analysis},
booktitle = {Advanced SAR Workshop 2011, Canadian Space Agency},
volume = {},
publisher = {},
url = {http://www.asc-csa.gc.ca},
isbn = {},
doi = {},
address = {Montreal (Saint-Hubert)},
pages = {6},
year = {2011},
month = {June},
abstract = {Image segmentation and unsupervised classification are difficult problems. We propose to combine both. A clustering process is applied over segment mean values. Only large segments are considered. The clustering is composed of a mean-shift step and a hierarchical clustering step. The hierarchical grouping is based upon a powerful segmentation technique previously developed [1]. The approach is applied on a 9-look polarimetric SAR image. Textured and non- textured image regions are considered. The K and Wishart distributions are used respectively. The unsupervised classification results can be very useful for image analysis and further supervised classification. The obtained region groups constitute an important simplification of the image.},
mypdf = {7},
keywords = {},
openpdf = {},
openid = {Beaulieu 2011}
}

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‪© 2011 Jean-Marie Beaulieu