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Image segmentation and unsupervised classification are difficult problems. We propose to combine both. A clustering process is applied over segment mean values. Only large segments are considered. The clustering is composed of a mean-shift step and a hierarchical clustering step. The hierarchical grouping is based upon a powerful segmentation technique previously developed. The approach is applied...
Recently, non-local approaches have proved very powerful for image denoising. Unlike local filters, the non-local (NL) means introduced in decrease the noise while preserving well the resolution. In the proposed paper, we suggest the use of a non-local approach to estimate single-look SAR reflectivity images or to construct SAR interferograms. SAR interferogram construction refers to the joint estimation...
We perform a full exploitation of the Differential SAR Interferometry (DInSAR) algorithm referred to as Small BAseline Subset (SBAS) technique to investigate long term surface deformation occurring in extended, seismogenetic areas. To this aim we benefit of the SBAS technique capability to work in multi-frame and multi-sensor scenarios in order to improve the spatial and temporal coverage, as well...
This paper presents an analysis of the performance of TerraSAR-X for subsidence monitoring in urban areas. The city of Murcia has been selected as a test-site due to its high deformation rate and the set of extensometers deployed along the city that provide validation data. The obtained results have been compared with those obtained from ERS/ENVISAT data belonging to the same period and validated...
Information mining from heavy SAR images is considered from the point of view of the procedure automatization. Two schemes based on Neural Networks are evaluated, one based on the Self Organizing Map method exploiting polarimetric information and oriented to land cover classification, the other based on the Pulse-Coupled Neural Networks aiming at characterizing the imaged buildings.
We develop a new SAR processor based on several orthogonal projections.We take into account the scattering properties of the target and the interferences by using subspace models. To detect the target without detecting the interferences, we process images from the orthogonal projection of the received signal into the target subspace and from the orthogonal projection of the received signal into a...
This paper is about evaluating the interest between studying directs dual images statistical indices and the use of statistical indices build from two SAR multipolarization images. We show an original way of using this kind of images by using two dimensionned statistical calculation in a Markov random field classification. We present results of our segmentation on urban, forest and mangrove areas...
We investigate the displacement phenomena affecting Mauna Loa and Kïlauea volcanoes at Big Island (Hawaii, USA), by applying an advanced ScanSAR-to-stripmap differential Synthetic Aperture Radar Interferometry (InSAR) approach. The implemented method, based on the application of the well-known Small BAseline Subset (SBAS) technique, allows the generation of LOS mean deformation velocity maps and...
PALSAR orthorectified HH and HV produced at 50m resolution is used for analysis. Since only two bands (HH and HV) have been limited in land cover discrimination, textures have been used as additional information for classification. This research derives second-order textures at different spatial resolutions and compares second-order textures at multiple scales to demonstrate their contributions in...
The National Research Council's decadal survey recommended DESDynI as one of the high priority missions for NASA. The mission envisions an InSAR/Lidar instrument for observing ecosystem structures on global scales with high spatial resolutions. Consistent and highly resolved global maps of biomass and carbon stocks require highly accurate observations of vegetation, in fact it is expected that such...
The objective of this article is to evaluate the influence of the cross-talk and channel imbalance calibration on the estimation of the entropy and the alpha images. Few studies can be found in SAR literature concerning the influence of the polarimetric image calibration process on the target decomposition methods and their consequences on the characterization and discrimination of different ground...
In the last years MultiDimensional (3D and 4D) Synthetic Aperture Radar (SAR) techniques, also known as SAR tomography and differential SAR tomography, are emerging in the field of coherent combination of multibaseline/multitemporal SAR data. With respect to the classical differential interferometric processing, these techniques improve the capability of detection and monitoring of the ground targets...
In the framework of remote-sensing image classification support vector machines (SVMs) have recently been receiving a very strong attention, thanks to their accurate results in many applications and good analytical properties. However, SVM classifiers are intrinsically noncontextual, which represents a severe limitation in image classification. In this paper, a novel method is proposed to integrate...
In order to expand the existing C-band SAR based damage estimation model into L-band SAR, this paper introduces a likelihood function to estimate severe damage ratio by earthquakes on the basis of dataset from JERS-1/SAR (L-band SAR) images observed the 1995 Kobe earthquake and its detailed ground truth data. The model is applied to JERS-1/SAR images taken over the tsunami affected areas by the 1993...
In this paper, a set of polarimetric eigenvalue and eigenvector based parameters, e.g. entropy and anisotropy, are investigated for forest application. The correlation terms of the eigenvectors, μ1 and μ2, are found to be better for forest mapping in both summer and winter using Radarsat-2 quad-polarimetric space borne SAR data. These are used to automatically identify forest class pixels from the...
This study investigates a new technique for land cover analysis by means of the Support Vector Machines. Intrinsic spatial variability within SAR images, beyond that caused by speckle, is of high interest for land cover characterization and classification. However, its use is still an ongoing issue due to its complex multi-scale nature. On the other hand, classification algorithms based on statistical...
The aimed accuracies for the final TanDEM-X DEM of 10m absolute and 2m relative height error will be ensured by calibration data. One crucial data set for the relative accuracy is tie-points that connect adjacent DEM acquisitions in the approximately 4km-overlap-area with each other. In this paper an improved concept for tie-point candidates is presented that is based on averaging a larger region...
In this study, an iterative maximum a posteriori (MAP) approach using a Bayesian model of Markovrandom field (MRF) was proposed for despeckling images that contains speckle. Image process is assumed to combine the random fields associated with the observed intensity process and the image texture process respectively. The objective measure for determining the optimal restoration of this “double compound...
This article compares four different alternative image representations in the context of a structure-based change detection. The framework is taken from the already published Curvelet-based change detection approach. Only the transform step is modified by inserting three additional transforms: the Laplacian pyramid, the Wavelet and the Surfacelet transform. The results of the change detection are...
Change detection represents an important tool in environmental monitoring and disaster management. Here, a novel unsupervised change-detection method is proposed for very high-resolution SAR images, by integrating wavelet multiscale feature extraction, Markov random fields for contextual modeling, and generalized Gaussian models. Experiments with COSMO-SkyMed data remark the effectiveness of the method...
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