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...

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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...

Remotely sensed images have already attained an important role in a wide spectrum of tasks ranging from weather forecasting to battlefield reconnaissance. One of the most promising remote sensing technologies is the imaging radar, known as synthetic aperture radar (SAR). SAR overcomes the nighttime limitations of optical cameras, and the cloud-cover limitations of both optical and infrared imag...

This paper presents an MPI-parallelized version of a matching algorithm for synthetic aperture radar (SAR) images. First the necessity for automated matching and the chosen algorithm are outlined briefly, and the algorithmic structure and the applied parallelization strategy are then presented and discussed. Performance results on a Cray T3D and a PowerChallenge from SGI are given, showing unex...

There is increasing interest in using synthetic aperture radar (SAR) images in automated target recognition and decision-making tasks. The success of such tasks depends on how well the reconstructed SAR images exhibit certain features of the underlying scene. Based on the observation that typical underlying scenes usually exhibit sparsity in terms of such features, this paper presents an image ...

Alternative data sources include scatterometry (Monaldo et al. 2004), or atmospheric model predictions (Monaldo et al. 2001). Figure 1 shows a wind speed map retrieved from an Envisat ASAR image acquired in wide swath mode (WSM) over Denmark on 13 October 2004. The image conveniently covers the majority of Danish Seas. A software tool developed at The Johns Hopkins University Applied Physics La...

This paper deals with the supervised classification of synthetic aperture radar (SAR) images. Our approach is based on two criteria, which explicitly take into account the intensity of the SAR image and the neighborhood classes, similarly to the Pots model, but weighted by a discontinuity map. The high level of noise involves numerous classification errors, then we classify a restored image fil...

In this paper we develop a method for synthetic-aperture radar (SAR) imaging through a dispersive medium. We consider the case when the sensor and scatterers are embedded in a known homogeneous dispersive material, the scene to be imaged lies on a known surface and the radar antenna flight path is an arbitrary but known smooth curve. The scattering is modeled using a linearized (Born) scalar mo...