Research Progress of Synthetic Aperture Radar Image Segmentation

Image segmentation is an indispensable part for synthetic aperture radar (SAR) image automatic interpretation.Segmentation results with high-quality are the guarantee of SAR image applications.In addition，owing to the development of SAR sensors，the segmentation task based on SAR image has been widely concerned in recent years.However，compared with the optical images，the unique properties of SAR images lead to great challenge in SAR image segmentation.With the development of pattern recognition，machine learning，remote sensing technology and other related techniques，SAR image segmentation has made great progress.This paper reviews the progress of SAR image segmentation，and then puts its emphasis on the summary of the widely used algorithms：FCM，MRF，statistical model，region information，level set，multi-scale and deep learning，etc.Finally，several viewpoints for the future research of SAR image segmentation are proposed.