Sparse Robust Filters for scene classification of Synthetic Aperture Radar (SAR) images

Two-Stage Multi-Task Representation Learning for Synthetic Aperture Radar (SAR) Target Images Classification

In this paper, we propose a two-stage multi-task learning representation method for the classification of synthetic aperture radar (SAR) target images. The first stage of the proposed approach uses multi-features joint sparse representation learning, modeled as a ℓ 2 , 1 -norm regularized multi-task sparse learning problem, to find an effective subset of training samples. Then, a new dictionary...

Polarimetric Synthetic Aperture Radar Data Classification Using Sparse Representation

Polarimetric synthetic aperture radar (PolSAR) data contain a large amount of potential information that is very appropriate for terrain classification. In this paper we proposed sparse representation approach to classify PolSAR data. Among a large number of PolSAR parameters we have chosen the most optimum parameters to form feature vector. Using k-means algorithm feature space is divided to C...

Understanding Synthetic Aperture Radar Images

Mapping by Airborne Synthetic Aperture Radar (sar)

Using advanced SAR data from the Danish airborne SAR, EMISAR, a research project was initiated in 1998 as a collaboration between the Technical University of Denmark and the Danish National Survey and Cadastre to investigate the potential of using SAR data for production and updating of cartographic maps. The ultimate objective of the research is to be able to perform quickly and efficiently co...

Synthetic Aperture Radar (SAR) ImagesProcessing: A Review

The Synthetic Aperture Radar (SAR) images are important application of optical satellite images because of its ability to operate in any weather conditions. This has applications in agriculture, geology, ecology, hydrology, oceanography and military, etc. With the improvement of SAR technology, the resolution of the images has increased. These images are corrupted by a strong noise, called Spec...