SAR image segmentation with active contours and level sets

Automatic interpretation of synthetic aperture radar (SAR) images requires automatic segmentation of these images. Image segmentation is a fundamental problem in computer vision, particularly difficult with SAR images because of the presence of strong, multiplicative speckle noise. The purpose of th...

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Bibliographic Details
Main Authors: Ayed, I.B., Vazquez, C., Mitiche, A., Belhadj, Z.
Format: Conference Proceeding
Language:English
Subjects:
Active contours
Applied sciences
Artificial intelligence
Computer science
control theory
systems
Computer vision
Equations
Exact sciences and technology
Histograms
Image segmentation
Level set
Pattern recognition. Digital image processing. Computational geometry
Robustness
Speckle
Synthetic aperture radar
Topology
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Description
Summary:Automatic interpretation of synthetic aperture radar (SAR) images requires automatic segmentation of these images. Image segmentation is a fundamental problem in computer vision, particularly difficult with SAR images because of the presence of strong, multiplicative speckle noise. The purpose of this study is to investigate a novel algorithm for segmenting a synthetic aperture radar (SAR) image into a fixed but arbitrary number of Gamma-homogeneous regions. This unsupervised algorithm is based on active contours and consists in evolving closed simple planar curves to minimize a criterion containing a term of conformity of data to a model of SAR image intensity and a term of regularization. The curve evolution equations are implemented via level sets for numerical stability and to allow variations in the topology of the curves during their evolution. Examples are given using real SAR images.
ISSN:1522-4880
2381-8549
DOI:10.1109/ICIP.2004.1421665