Segmentation and target recognition in SAR imagery using a level-sets-multiscale-filtering technique

Using salient features to drive image filtering is an important problem in image analysis and computer vision. The notion of a scale space has as a result gained popularity on account of its advantage in providing a dynamic description of image features. Object or shape information is inherently contained in level sets or level curves of an image, and its preservation while removing noise can be done reliably through processing of level sets of an image instead of directly working on its intensity values. Following this argument, and the fact that SAR images are impulsive in nature, we propose a level-set-based multiresolution filtering technique for segmentation of SAR imagery. Extracted target information of images, from various radar view angles are integrated to build up an overall target silhouette, which is then used for classification of two main target vehicle types.