In previous work we have developed a methodology for texture recognition and synthesis that estimates and exploits the dependencies across scale that occur within images.1,2 In this paper we discuss the application of this technique to synthetic aperture radar (SAR) vehicle classification. Our approachmeasures characteristic cross-scale dependencies in training imagery; targets are recognized w...

In this paper we introduce a new approach for recovering shape-from-shading (SFS) from synthetic aperture radar (SAR) images of the terrain. Three contributions are proposed. Firstly, we show how the direction of surface normals is constrained by the geometry of the radar reflectivity cone. Second, we show how topographic features can be used as boundary constraints on the recovered surface nor...

During the last two decades synthetic aperture radar (SAR) and interferometric synthetic aperture radar (InSAR) have become important tools for airborne and satellite remote sensing. SAR delivers a high resolution image of the radar backscatter and by means of InSAR a second image from almost the same orbit is combined with the first one to provide the relative phase difference and stability/co...

We develop a method for the formation of spotlight-mode synthetic aperture radar (SAR) images with enhanced features. The approach is based on a regularized reconstruction of the scattering field which combines a tomographic model of the SAR observation process with prior information regarding the nature of the features of interest. Compared to conventional SAR techniques, the method we propose...

Accurate sea-ice segmentation from satellite synthetic aperture radar (SAR) images plays an important role for understanding the interactions between sea-ice, ocean and atmosphere in the Arctic. Processing sea-ice SAR images are challenging due to poor spatial resolution and severe speckle noise. In this paper, we present a multi-stage method for the sea-ice SAR image segmentation, which includ...

Autonomous navigation airborne forward-looking synthetic aperture radar (SAR) observes the anterior inferior wide area with a short cross-track dimensional linear array as azimuth aperture. This is an application scenario that is drastically different from that of side-looking space-borne or air-borne SAR systems, which acquires azimuth synthetic aperture with along-track dimension platform mov...

Speckle noise (salt and pepper) is inherent to synthetic aperture radar (SAR), which causes a usual noise-like granular aspect and complicates the image classification. In SAR image analysis, the spatial information might be a particular benefit for denoising and mapping classes characterized by a statistical distribution of the pixel intensities from a complex and heterogeneous spectral respon...

1 Abstract— In this paper the Modified Fractal Signature (MFS) method is applied to real Synthetic Aperture Radar (SAR) images provided to our research group by SET 163 Working Group on SAR radar techniques. This method uses the 'blanket' technique to provide useful information for SAR image classification. It is based on the calculation of the volume of a 'blanket', corresponding to the image ...

he high resolution and large coverage of satellite synthetic aperture radar (SAR) offer a unique opportunity to derive mesoscale wind fields over the ocean surface and to investigate their spatial variation. For this purpose, different algorithms were developed and tested using SAR images from two European Remote Sensing satellites. In this article, the methods for deriving wind fields from SAR...

The most distinctive characteristic of synthetic aperture radar (SAR) is that it can acquire data under all weather conditions and at all times. However, its coherent imaging mechanism introduces a great deal of speckle noise into SAR images, which makes the segmentation of target and shadow regions in SAR images very difficult. This paper proposes a new SAR image segmentation method based on w...