1,720,959 research outputs found
Contextual Tomographic SAR Denoising Approach for Estimating Scatterers’ Height and Deformation Velocity
No full textThe reliability of tomographic synthetic aperture radar (TomoSAR) products depends on the quality of complex-valued tomographic interferograms. The latter is unfortunately affected by noise from various sources. In order to reduce their impact and thus improve the outcome, filtering methods can be implemented at different levels of the TomoSAR process. In this article, we propose the application of a contextual denoising approach in transformed domains, based on subband decomposition and nonlinear weighting, with the aim to study its influence on TomoSAR height and deformation velocity estimation using generalized likelihood ratio test detection. Both spatial and spatiotemporal arrangements of overlapping blocks are considered in wavelet domains. The nonlinear filtering parameter is estimated from the coherence and/or pseudo-correlation (CPC) indicators. In order to show the effectiveness of the approach, the obtained findings have been compared to the state-of-the-art methods, namely, Goldstein and Baran filters. The assessment of the results with respect to denoising and TomoSAR evaluation metrics was carried out using both simulated and real data acquired by TerraSAR-X (TSX) satellite over the city of Naples
Adaptive Coherent Multilook GLRT for SAR Tomography Detection
No full textIn recent years, generalized likelihood ratio test (GLRT) scatterers’ detection in the context of synthetic aperture radar tomography (TomoSAR) has gained great interest from the remote sensing scientific community. This is due to its effectiveness in identifying scatterers within each single azimuth–range resolution cell, particularly in urban areas. The multilook GLRT (M-GLRT) variant offers more satisfactory results at the expense of spatial resolution deterioration, by jointly exploiting the neighboring information of the pixel to be reconstructed. In this context, coherent and incoherent formulations can be adopted. The former provides better performance in the assumption of constant reflectivity of the pixels in the considered neighborhood, while the latter is much more robust with respect to the violation of this assumption. In this article, an adaptive formulation of the coherent and incoherent GLRT is presented with the aim of improving scatterers’ detection and their height estimation. The method is based on an adaptive window setting, to select adjacent pixels with similar height and reflectivity characteristics. A detailed study and analysis of the proposed adaptive coherent M-GLRT (ACM-GLRT) detector has been conducted and validated through simulations along with comparison to both standard and adaptive formulations of incoherent M-GLRT. Experimental findings from a real dataset acquired by the German TerraSAR-X (TSX) over the city of Naples (Italy) demonstrate the performance improvement of our proposed approach
Adaptive quality indicator for subband multi-baseline TomoSAR filter
No full textThe development of Synthetic Aperture Radar (SAR) techniques has been ongoing for a few decades due to the continuous expansion of SAR technologies. However, the source of decorrelations among other noise artefacts constitutes one of the main limitations to all interferometric-based processes including Tomography (TomoSAR). As a consequence, the interpretation of generated height maps and 3D point clouds is challenging, particularly with the difficulty of obtaining accurate in-situ measurements for validation. To address this issue in urban areas, a few works proposed the use of a filtering approach in order to facilitate the application of TomoSAR inversion or detection methods. At our end, we propose an improved version of multi-baseline Goldstein-based filter through its application in the wavelet domain, on the one hand, and the adaptive estimation of the alpha parameter, on the other hand. The generated height maps and point clouds using a limited number of images acquired by TerraSAR-X sensor are evaluated qualitatively and quantitatively. Edge preservation index and standard deviation showed the effectiveness of the approach with respect to the filtering criteria, while the R-squared and detection rate illustrated its efficiency in terms of height estimation. Both assessments demonstrated the performance of the proposed denoising methodology
Spatio-Temporal Filtering Approach for Tomographic SAR Data
No full textSynthetic aperture radar tomography (TomoSAR) has recently received particular interest from the remote-sensing community, due to its ability to provide 3-D reconstructions of environments with complex structures. Unfortunately, different forms of decorrelations and processing errors affect the quality of the resulting 2-D/3-D images. One way to cope with the impact of these nuisances is to apply appropriate filtering to the interferometric data stack as a preprocessing step. The first obstacle to be dealt with, especially in urban areas, is to define a filter whose parameters have to be set in such a way as to improve smoothing capabilities while preserving edges. To this aim, the main objective of this article is twofold: 1) the application of a spatio-temporal contextual filter whose parameters depend on 3-D quality indicators of the multibaseline interferometric image stack and 2) evaluation of the denoising effect on the application of nonparametric spectral estimation and detection algorithms. For that, we consider several quantitative metrics to assess, on the one hand, the filtering performances, and, on the other hand, its impact on the reflectivity function recovered from conventional tomographic inversion and detection methods. Experimental results from a set of TerraSAR-X (TSX) images highlight the efficiency of the filtering process by improving the scatterers' detection and height localization, of a man-made structure
Generalized Parametric Iterative Approach for Tomographic SAR Reconstruction
No full textThe reconstruction of high-elevation natural and artificial structures through synthetic aperture radar (SAR) tomography has been an active research topic owing to its significance in various earth science applications. However, the complexity of this task arises from inaccuracies in the estimated reconstruction, attributed to factors such as low signal-to-noise ratios, decorrelations, few and uneven measurements, and overlapping scatterers. The utilization of iterative spectral estimation methods has been demonstrated to be beneficial in addressing some of these inaccuracies. Thus, selecting the best method within this class constitutes a challenge. In this context, our letter aims to propose a generalized formula linking the maximum likelihood (ML)-based iterative methods via a regularization parameter. The behavior of the latter is analyzed for several values to unveil the potential of the proposed approach in achieving a balance between noise reduction and detection performance. The experimental study has been conducted on simulated and real SAR data acquired by airborne and spaceborne systems covering tropical forests and build-up areas. The obtained results show the effectiveness and performance of the optimal regularization parameter to eliminate noise while preserving the scatterers' contribution
Gridless GLRT For Tomographic SAR Detection Using Particle Swarm Optimization Algorithm
No full textThe detection of multiple scatterers within each resolution cell is an open research subject in synthetic aperture radar (SAR) tomography (TomoSAR). For over a decade, the generalized likelihood ratio test (GLRT) detector has been implemented along with its variants, allowing the generation of height maps and 3-D point clouds with good precision. However, they are limited by the grid search during the optimization of the maximum likelihood function. In order to mitigate this, we propose a gridless version of GLRT where the particle swarm optimization (PSO) method is used to locate the minima. The conducted analysis of the proposed detector with respect to the state-of-the-art methods behavior on simulated and real datasets proved the effectiveness of PSO-GLRT in terms of height accuracy and computational cost. The evaluation metrics, root-mean-square error (RMSE), accuracy, and completeness, have been used as a quantitative improvement indicator for estimated height assessment
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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