Abstract
Synthetic Aperture Radar (SAR) images are dificult to segment due to their characteristic noise, called speckle, which is multiplicative, non-gaussian and has a low signal to noise ratio. In this work we use the \(\mathcal{G}^{H}\) distribution to model the SAR data from the different regions of the image. We estimate their statistical parameters and use them in a segmentation algorithm based on multiregion competition. We then apply this algorithm to segment simulated as well as real SAR images and evaluate the accuracy of the segmentation results obtained.
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© 2009 Springer-Verlag Berlin Heidelberg
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Buemi, M.E., Goussies, N., Jacobo, J., Mejail, M. (2009). SAR Image Segmentation Using Level Sets and Region Competition under the \(\mathcal{G}^H\) Model. In: Bayro-Corrochano, E., Eklundh, JO. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2009. Lecture Notes in Computer Science, vol 5856. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10268-4_18
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DOI: https://doi.org/10.1007/978-3-642-10268-4_18
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