Polarimetric SAR Image Segmentation with B-Splines and a New Statistical Model

Abstract

We present an approach for polarimetric Synthetic Aperture Radar (SAR) image region boundary detection based on the use of B-Spline active contours and a new model for polarimetric SAR data: the GHP distribution. In order to detect the boundary of a region, initial B-Spline curves are specified, either automatically or manually, and the proposed algorithm uses a deformable contours technique to find the boundary. In doing this, the parameters of the polarimetric GHP model for the data are estimated, in order to find the transition points between the region being segmented and the surrounding area. This is a local algorithm since it works only on the region to be segmented. Results of its performance are presented.

References in corpus (1)

• Hypothesis Testing in Speckled Data with Stochastic Distances

Cited by in corpus (7)

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• Entropy-based Statistical Analysis of PolSAR Data
• Information Theory and Image Understanding: An Application to Polarimetric SAR Imagery
• Bias Correction and Modified Profile Likelihood under the Wishart Complex Distribution
• Interval edge estimation in SAR images