Results 31 to 40 of about 7,181 (241)
On the use of the l(2)-norm for texture analysis of polarimetric SAR data [PDF]
, 2016 In this paper, the use of the l2-norm, or Span, of the scattering vectors is suggested for texture analysis of polarimetric synthetic aperture radar (SAR) data, with the benefits that we need neither an analysis of the polarimetric channels separately ...
Deng, xinping, López Martínez, Carlos
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Convolutional neural network (CNN) has achieved remarkable success in polarimetric synthetic aperture radar (PolSAR) image classification. However, the PolSAR image classification is a pixelwise prediction assignment.
Feng Zhao +3 more
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Remote Sensing, 2022 The radiometric terrain correction (RTC) is an essential processing step for supervised classification applications of polarimetric synthetic aperture radar (PolSAR) over mountainous areas.
Lei Zhao +4 more
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Coherency Matrix Decomposition-Based Polarimetric Persistent Scatterer Interferometry [PDF]
, 2019 © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new ...
Mallorquí Franquet, Jordi Joan +1 more
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Simulation of shoreline change using AIRSAR and POLSAR C-band data [PDF]
, 2011 This paper presents a new approach for modeling shoreline change due to wave energy effects from remotely sensed data. The airborne AIRSAR and POLSAR data were employed to extract wave spectra information and integrate them with historical remotely ...
Cracknell, Arthur +2 more
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Adaptive Speckle Filter for Multi-Temporal PolSAR Image with Multi-Dimensional Information Fusion
Remote Sensing, 2023 Polarimetric synthetic aperture radar (PolSAR) is an important sensor for earth observation. Multi-temporal PolSAR images obtained by successive observations of the region of interest contain rich polarimetric–temporal–spatial information of the land ...
Haoliang Li +4 more
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Deep learning in remote sensing: a review [PDF]
, 2017 Standing at the paradigm shift towards data-intensive science, machine learning techniques are becoming increasingly important. In particular, as a major breakthrough in the field, deep learning has proven as an extremely powerful tool in many fields ...
Fraundorfer, Friedrich +6 more
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PolSAR Image Classification via Learned Superpixels and QCNN Integrating Color Features
Remote Sensing, 2019 Polarimetric synthetic aperture radar (PolSAR) image classification plays an important role in various PolSAR image application. And many pixel-wise, region-based classification methods have been proposed for PolSAR images.
Xinzheng Zhang +4 more
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Classification of Polarimetric SAR Images Based on the Riemannian Manifold
Leida xuebao, 2017 Classification is one of the core components in the interpretation of Polarimetric Synthetic Aperture Radar (PolSAR) images. A new PolSAR image classification approach employs the structural properties of the Riemannian manifold formed by PolSAR ...
Yang Wen +3 more
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Analytic Expressions for Stochastic Distances Between Relaxed Complex Wishart Distributions [PDF]
, 2013 The scaled complex Wishart distribution is a widely used model for multilook full polarimetric SAR data whose adequacy has been attested in the literature.
Cintra, Renato J. +2 more
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