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Water surface extraction using satellite images proves to be of great importance due to its utility in several applications such as land use, floods management and monitoring. Among the wide range of sensors orbiting around the earth, Synthetic Aperture Radar (SAR) proves to be a very effective tool in this context due to its robustness to unfavorable weather conditions and its cloud penetrating capabilities...
Forest monitoring is a major concern today due to climate changes, conservation of fauna and flora and to the lack of water[1]. Therefore, several environmental monitoring techniques have been developed and used to detect changes in the scenes. The use of SAR is appropriate to detect changes due to its independence of atmospheric and lighting conditions. However, currently, also SAR change detection...
Statistical modeling of Synthetic Aperture Radar (SAR) images is an important tool for image processing and interpretation, because it can contribute to a better understanding of the terrain electromagnetic scattering mechanisms. To that end, the G0I distribution is able to characterize a large number of targets. This distribution depends on three parameters: texture, scale, and the number of looks...
The availability of synthetic aperture radar (SAR) data with high spatial resolution offers great potential for environmental monitoring due to the insensitivity of SAR to atmospheric and sunlight-illumination conditions. In this paper, an unsupervised change detection method for SAR images at medium to high resolution is proposed. The image ratioing approach is adopted, and a Bayesian unsupervised...
Speckle noise is an inherent problem in synthetic aperture radar (SAR) images. Recently, non-local (NL) means performs well in speckle reduction. However, there exist two issues in traditional NL means. Speckle noise and strong targets would affect the correctness, thus resulting in over smoothing and speckles unchanged. In this paper, an improved algorithm combined with wavelet transform and adaptive...
This paper aims at the feature enhancement for the multichannel synthetic aperture radar (SAR) images. A novel non-local vectorial total variation approach, which is an extension of the non-local vectorial total variation approach for the multichannel SAR images, is proposed. It contains the vectorial data fidelity term and the non-local vectorial total variation term. The non-local vectorial total...
Coastline extraction in Synthetic aperture radar (SAR) images is a fundamental and challenging task due to the speckle noise. In this paper, we propose a new method for automatic coastline extraction in SAR images. In our method, we combine K-means and speckle noise removal methods together to increase the dissimilarity between sea and land. To enhance the robustness to speckle noise, and preserve...
Among the advanced applications of polarimetric synthetic aperture radar (PolSAR), automatic target recognition (ATR) is a very challenge topic. Conventional target detection algorithms such as constant false alarm rate (CFAR) or support vector machines [1]–[4], where the detector is applied in pixel-by-pixel manner and only pixel-wise scattering signatures, single-channel intensity or multi-channel...
Submarine detection plays an important role in modern wars. As a potential technique, synthetic aperture radar (SAR) is used to detect submarines through detecting their wakes on the sea surface. This requires the images of submarine wakes under all kinds of conditions. However, it is difficult to acquire these images by field experiment. In this paper, we propose a method to simulate SAR images of...
The combination of the polarimetric information with time observations represents an extremely valuable tool for the different applications of polarimetric SAR images. One of the most important preprocessing steps in this context is speckle filtering. In this paper, a new method to multitemporal multidimensional (MTMD) speckle filter covariance matrices of polarimetric SAR data is presented. MTMD...
This paper presents a method for strong scatterers change detection in synthetic aperture radar (SAR) images based on a decomposition for multi-temporal series. The formulated decomposition model jointly estimates the background of the series and the scatterers. The decomposition model retrieves possible changes in scatterers and the date at which they occurred. An exact optimization method of the...
Speckle noise is an inherent problem in synthetic aperture radar (SAR) imaging system. For further imagery analysis and interpretation, it demands better and more efficient polarimetric SAR (PolSAR) speckle-filtering algorithms. Inspired by the great success of stochastic denoising, our goal in this paper is to reduce speckle noise of PolSAR image with random walk model. Taking spatial distance into...
Wind direction is a crucial parameter in many inversion models to estimate wind speed from Synthetic Aperture Radar (SAR) data. Compared to the other available wind sources, i.e. measured data, numeric weather data, etc., the retrieval of wind directions from SAR data is more widely used, since it can give wind directions at different scales. Nevertheless, there are not a lot of studies which report...
A novel despeckling algorithm for synthetic aperture radar (SAR) image is presented. This algorithm focuses on despeckling a local region for each target pixel. Thus, the calculations of similarities and weights are located within a limited region rather than the entire image. Also, the similarity is measured by using the Euclidean distance of features between the target pixel and neighborhood pixel...
Speckle existed in SAR image is an undesirable product of specific imaging principle which influences SAR image interpretation and processing. In this paper, a new SAR image denoising algorithm has been proposed combining cluster with sparse representation under the non-local methodology. Due to the similar clustered patches, the sparsity coding of clustered patches is sparser. And clustered patches...
In this paper, we extend the product model from common texture to the case of multitexture. With the generalized Gamma distribution (GΓD) being the texture distribution, a multitexture model for multilook polarimetric SAR data is proposed and the estimation of parameters is performed based on the method of matrix log-cumulant. As far as the diagonal random texture matrix is concerned, the textures...
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