Novel Method for SAR Image Segmentation with Application to Bridge Detection

A new method for SAR image segmentation is proposed in this paper. Region segmentation can be achieved by contour tracking, and we use the general Bayesian tracking framework to solve this problem. Due to the non-linearity of the tracking problem and the non-Gaussian noise of SAR image, Monte Carlo based particle filtering algorithm is adopted to obtain the Bayesian optimal solution. Based on the tracking framework, a particle filter based contour tracking method is proposed for region segmentation in SAR images. In this method, each particle is assigned to a linear segment with specific location and direction. The response of the local edge detector is used to calculate the particle weight while the global contextual knowledge, such as the smoothness of the region boundary, is guaranteed by the propagation of particles. The proposed method is employed for river boundary extraction on the SAR image. Furthermore, bridges over a river are detected