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An automatic approach to detect bilge dumping in synthetic aperture radar (SAR) images over Southern African oceans is proposed. The approach uses a threshold-based algorithm and a region-based active contour model (ACM) algorithm to achieve an efficient bilge dump detection tool. A threshold method was used to detect areas with a high bilge dump probability while the ACM method is used to get closed...
This paper has proposed a new method that integrates the advantage of optical image for delineating land surface boundaries and the superiority of PolSAR data for obtaining corn information despite bad weather conditions. The comparison between the proposed method and both pixel- and object-based method was made to test their performance for corn classification. The analysis shows that the proposed...
This letter depicts a ship detection scheme for synthetic aperture radar images, utilizing a segmentation based global iterative censoring algorithm. In the proposed scheme, the fuzzy local information c-means clustering (RFLICM) algorithm is adopted to partition the inhomogeneous SAR image into numerous homogeneous sub-regions, thereby eliminating the performance degradation caused by SAR image inhomogeneity...
COSMO-SkyMed (Constellation of Small satellites for Mediterranean basin Observation) is a fundamental, powerful asset to Earth Observation field, in which Italy plays a crucial role at world level. It is an Earth Observation Dual Use System (civil and military) conceived to fulfill both civilian and defense needs, enhancing international partnerships through its Interoperability, Expandability and...
In this paper, we propose a fast PolSAR image superpixel segmentation method. This method takes a simple coarse-to-fine optimization technique to minimize a Markov-Random-Field (MRF) like energy function which integrates the Pol- SAR image statistic, spatial position and boundary smoothing. It updates boundary of superpixels staring with a large block level and iterates down to the final pixel level...
Land cover change detection has long been a hot field in polarimetric synthetic aperture radar (SAR) applications. In certain cases, we care not only the changed areas but also from which type to another. This paper presents a supervised urban land cover change types identification method using a series of polarimetric descriptors from SAR observables and polarimetric decomposition. The normalized...
This paper proposes an iterative unsupervised Markov Random Field (MRF) based segmentation technique for polarimetric Synthetic Aperture Radar (SAR) image using the optimized scattering mechanism similarity parameters. Parameter estimation for the MRF model is generally performed from the available training data in order to perform tasks including semantic image segmentation. Since the current scenario...
In this paper, a method for road detection based on Duda and path operators has been presented. The roads are represented as slender dark regions with constant width and reflectance in the high-resolution SAR images. The path operators (path openings and closings) were performed as morphological filters in retaining linear structures. However, the filters were not sensitive to the width of linear...
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...
Remote sensing has been widely applied for environmental monitoring by means of change detection techniques, commonly for identifying deforestation signs which is the gateway for illegal activities such as uncontrolled urban growth and grazing pasture. Monthly acquired X-Band images from airborne Synthetic Aperture Radar (SAR) provided multi-temporal scenes employed in this work resulting in environmental...
A novel unsupervised, non-Guassian and contextual clustering algorithm for segmentation of polarimetric SAR images has been presented in [1]. This represents one of the most advanced PolSAR unsupervised statistical segmentation algorithm and uses the doubly flexible, two parameter, U-distribution model for the PolSAR statistics. However complexity of the probability density function leads to high...
In this paper, we investigate the role of polarimetric features to improve flood mapping in agricultural areas. Considering that the double bounce enhancement due to standing water can increase the backscatter from flooded agricultural fields, polarimetry can potentially detect this mechanism and mitigate the misdetection of algorithms based on the identification of dark areas in the image. The investigation...
Sea ice charts are provided operationally by the Canadian Ice Service (CIS) for the convenience of people in high-latitude regions. Hence, approaches to ice-water discrimination are in demand. An approach is proposed in this paper, in which no manual interpretation is involved in the selection of training data. It is done based on the discrepancy of incidence angle dependence between sea ice and open...
The mean shift algorithm shows a good performance in optical image segmentation. However, conventional mean shift algorithm performs poorly if it is used directly to synthetic aperture radar (SAR) image due to the large dynamic range and strong speckle noise. Recently, a generalized mean shift (GMS) algorithm with an adaptive variable asymmetric bandwidth was proposed for polarimetric SAR (PolSAR)...
The detection of ocean oil spill based on synthetic aperture radar (SAR) image has been a hot topic attracting extensive attention. In this paper, a hybrid scheme, in which we extract feature parameters and then achieve classification as follows, is presented. Two-dimensional (2-D) Otsu algorithm is applied in image segmentation process, and neural network is applied in classification course. Before...
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