Polarimetric SAR Image Segmentation with B-Splines and a New Statistical Model
This work addresses region boundary detection in polarimetric SAR images, which is an incremental improvement for remote sensing applications.
The paper tackles the problem of segmenting polarimetric SAR images by developing an approach using B-Spline active contours and a new statistical model called the GHP distribution to detect region boundaries, with results demonstrating its performance.
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.