[Bea2004b]
Utilisation of Contour Criteria in Micro-Segmentation of SAR Images

Author:Beaulieu Jean-Marie

Journal:International Journal of Remote Sensing

 Sept. 2004, vol. 25, issue 17, p. 3497–3512

ISSN:0143-1161

URL:http://www.tandfonline.com/doi/abs/10.1080/01431160310001647714

DOI:10.1080/01431160310001647714

Abstract:   The segmentation of SAR (Synthetic Aperture Radar) images is greatly complicated by the presence of coherent speckle. To carry out this process a hierarchical segmentation algorithm based on stepwise optimization is used. It starts with each individual pixel as a segment and then sequentially merges the segment pair that minimizes the criterion. In a hypothesis testing approach, we show how the stepwise merging criterion is derived from the probability model of image regions. The Ward criterion is derived from the Gaussian additive noise model. A new criterion is derived from the multiplicative speckle noise model of SAR images. The first merging steps produce micro-regions. With standard merging criteria, the high noise level of SAR images results in the production of micro-regions that have unreliable mean and variance values and irregular shapes. If the micro-segments are not correctly delimited then the following steps will merge segments from different fields. In examining the evolution of the initial segments, we see that the merging should take into account spatial aspects. In particular, the segment contours should have good shapes. We present three measures based on contour shapes, using the perimeter, the area and the boundary length of segments. These measures are combined with the SAR criterion in order to guide correctly the segment merging process. The new criterion produces good micro-segmentation of SAR images. The criterion is also used in the following merges to produce larger segments. This is illustrated by synthetic and real image results.

@Article{Bea2004b,
author = {Beaulieu, Jean-Marie},
title = {Utilisation of Contour Criteria in Micro-Segmentation of {SAR} Images},
journal = {International Journal of Remote Sensing},
volume = {25},
number = {17},
pages = {3497--3512},
year = {2004},
month = {Sept.},
abstract = {The segmentation of SAR (Synthetic Aperture Radar) images is greatly complicated by the presence of coherent speckle. To carry out this process a hierarchical segmentation algorithm based on stepwise optimization is used. It starts with each individual pixel as a segment and then sequentially merges the segment pair that minimizes the criterion. In a hypothesis testing approach, we show how the stepwise merging criterion is derived from the probability model of image regions. The Ward criterion is derived from the Gaussian additive noise model. A new criterion is derived from the multiplicative speckle noise model of SAR images. The first merging steps produce micro-regions. With standard merging criteria, the high noise level of SAR images results in the production of micro-regions that have unreliable mean and variance values and irregular shapes. If the micro-segments are not correctly delimited then the following steps will merge segments from different fields. In examining the evolution of the initial segments, we see that the merging should take into account spatial aspects. In particular, the segment contours should have good shapes. We present three measures based on contour shapes, using the perimeter, the area and the boundary length of segments. These measures are combined with the SAR criterion in order to guide correctly the segment merging process. The new criterion produces good micro-segmentation of SAR images. The criterion is also used in the following merges to produce larger segments. This is illustrated by synthetic and real image results.},
publisher = {},
url = {http://www.tandfonline.com/doi/abs/10.1080/01431160310001647714},
issn = {0143-1161},
doi = {10.1080/01431160310001647714},
mypdf = {11},
address = {},
keywords = {},
openpdf = {},
openid = {Semantics}
}

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Received: 24 Jun 2002
Accepted: 16 Jul 2003
Published: SEP 2004
Published online: 04 Jun 2010
Publisher: TAYLOR & FRANCIS LTD, 4 PARK SQUARE, MILTON PARK,ABINGDON OX14 4RN, OXON, ENGLAND
Research Areas: Remote Sensing; Imaging Science & Photographic Technology Web of Science Categories: Remote Sensing; Imaging Science; Photographic Technology
Document Type: Article
Language:English
Accession Number: WOS:000222519500011 ISSN: 0143-1161 print/ISSN 1366-5901 online