Automated interpretation of very-high resolution SAR images

Abstract

Very-high resolution (VHR) synthetic aperture radar (SAR) images from the last generation satellites such as TerraSAR-X and TanDEM-X exhibits special characteristics, especially in the urban-areas. Consequently, attention is needed on special considerations while developing algorithms for SAR image processing and its applications for automated interpretation. With automatic interpretation we refer to the information extraction and characterization for image categorization, retrieval, segmentation, automated target recognition etc.. In this article we focus our attention to the problem of SAR image categorization. The interest in SAR image categorization in VHR SAR (on the contrary to the pixel-based classification in low-resolution SAR images) has increased with enhanced resolution providing opportunity to carry out a more detailed analysis of targets and objects. SAR image categorization requires generation of a compact feature descriptor which accurately define the image content. A feature descriptor can be generated using `parametric' or `non-parametric' approaches in `image' or `image within a transformation space'. The objective of this article is to review some selected techniques for this purpose in form of a methodological classification. Qualitative assessment of selected algorithms is presented.