Generic object recognition in high resolution SAR images

This paper presents a non-parametric modeling scheme for high resolution SAR data, based on Short Time Fourier Transform which is able to integrate the radiometrical and morphological properties of the data, for object recognition, scene and target indexing, addressing the problem of large data base queries and information retrieval.. The method is assessed by using a Bayesian Support Vector Machine image search engine based on a hierarchical learning model. The method allowed for the recognition of over 30 different classes, both homogeneous and heterogeneous urban objects with high levels of details. Qualitative and quantitative measures for evaluation are presented and discussed.