Constellations of Synthetic Aperture Radar (SAR) satellites with short repeat time acquisitions allow exploration of active faults behavior with unprecedented temporal resolution. Along the North Anatolian Fault (NAF) in Turkey, an 80 km long section has been creeping at least since the 1944, Mw 7.3 earthquake near Ismetpasa, with a current Interferometric Synthetic Aperture Radar (InSAR)-deriv...

We investigate the effects of phase errors on undersampled synthetic aperture radar (SAR) systems. We show that the standard methods of auto-focus, which are used as a postprocessing step, are typically not suitable. Instead of applying auto-focus as a post-processor we propose using a stable algorithm, which is based on algorithms from the dictionary learning literature, that corrects phase er...

A directional filter algorithm for intensity synthetic aperture radar (SAR) image based on nonsubsampled contourlet transform (NSCT) and immune clonal selection (ICS) is presented. The proposed filter mainly focuses on exploiting different features of edges and noises by NSCT. Furthermore, ICS strategy is introduced to optimize threshold parameter and amplify parameter adaptively. Numerical exp...

Synthetic Aperture Radar (SAR) technology is mainly used to obtain high-resolution images of ground areas in resolutions even less than meter. SAR is even capable of imaging a wide area of terrain and from two and more images it is possible to reconstruct a 3D digital elevation model of ground terrain. Good thing about SAR is an all whether operation and possibility to capture images under vari...

Remote sensing applications such as Ecological monitoring, Disaster monitoring, Volcanic monitoring, surveillance and reconnaissance requires broad range imaginary data with very high resolution. Data captured under different times such as day or night and under different weather conditions poses adverse affects on retrieved results. Synthetic Aperture Radar (SAR) technology is used to mitigate...

In this paper we develop a supervised classification approach for medium and high resolution multichannel synthetic aperture radar (SAR) amplitude images. The proposed technique combines finite mixture modeling for probability density function estimation, copulas for multivariate distribution modeling and a Markov random field (MRF) approach to Bayesian classification. The novelty of this resea...

Owing to significant differences in synthetic aperture radar (SAR) images caused by diverse imaging mechanisms and imaging conditions, inconsistent features and relationship correspondences constitute key problems for traditional image registration algorithms. This study presents a novel SAR image registration method based on the shape information of distinct ground objects, which is obtained v...

In this paper we develop a novel classification approach for high and very high resolution polarimetric synthetic aperture radar (SAR) amplitude images. This approach combines the Markov random field model to Bayesian image classification and a finite mixture technique for probability density function estimation. The finite mixture modeling is done via a recently proposed dictionary-based stoch...

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...

study on polsar target detection essentially requires the cattering information and polarimetric statistical data. theoretical analysis shows that some terms of the second order scattering matrices such as coherence and covariance matrix clearly show the differences between nonsymmetrical man-made objects and natural clatters which being reflection symmetric. using the model derived from these ...