Results 161 to 170 of about 7,886 (195)

Three-component decomposition for polarimetric SAR

2009 IEEE International Geoscience and Remote Sensing Symposium, 2009
An improved three-component decomposition for polarimetric SAR data is proposed in this paper. The reasons of the emergence of negative powers in the Freeman decomposition have been analyzed, and two improvements are included. Firstly, the deorientation process is applied to the coherency matrix before it is decomposed into three scattering components.
Wentao An, Yi Cui, Jiang Yang
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Polarimetric sar target decomposition based on nonlinear decorrelation

2012 Tyrrhenian Workshop on Advances in Radar and Remote Sensing (TyWRRS), 2012
In remotely sensed Synthetic Aperture Radar (SAR) images, scattering from a target is often the result of a mixture of different scattering mechanisms. Fully polarimetric data offers the possibility to separate and to interpret them. To achieve this task, several target decomposition techniques have been proposed in the literature.
Licciardi, GA, Avezzano, RG, DEL FRATE, FABIO, SCHIAVON, GIOVANNI, Chanussot, J.   +4 more
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Preliminary results of a new polarimetric decomposition based on polarimetric signatures

2014 IEEE Geoscience and Remote Sensing Symposium, 2014
The polarimetric decomposition is one of the key steps of SAR data processing and analysing. Its aim is to obtain maximum information about different scattering mechanisms that occur within each resolution cell of radar image. Since now, there has been a several decomposition methods proposed in the literature. The most widely used are H/A/α, Yamaguchi,
Stanislawa Porzycka-Strzelczyk, Jacek Strzelczyk, Maciej Dwornik, Andrzej Lesniak   +3 more
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Model-based polarimetric decomposition using PolInSAR coherence

2011 IEEE International Geoscience and Remote Sensing Symposium, 2011
A volume scattering model utilizing polarimetric SAR interferometry (PolInSAR) coherence is proposed. The new model is more adaptive and better fit for both forest and skew-oriented built-up areas. Thereby, a new model-based polarimetric decomposition scheme is developed. The advantage of the proposed method is demonstrated by E-SAR PolInSAR data.
Si-Wei Chen, Motoyuki Sato
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Polarimetric target scattering decomposition: A review

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016
The most popular model-based decompositions (MBD) are reconsidered in the context of the estimation theory. It is shown that a large processing window is required to reduce the bias on the individual scattering contribution due the target scattering Reflection symmetry assumption.
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Biomass retrieval based on polarimetric target decomposition

2011 IEEE International Geoscience and Remote Sensing Symposium, 2011
Former NASA's Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI) satellite mission was to provide regional or global biomass carbon stock at regional, national, and global scales. Carbon Monitoring System UAVSAR and LVIS data acquired in August 2009 were used in this paper.
Zhiyu Zhang, Yong Wang, Guoqing Sun, Wenjian Ni, Wenli Huang, Lixin Zhang   +5 more
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Landslides identification based on polarimetric decomposition techniques using Radarsat-2 polarimetric images

International Journal of Remote Sensing, 2015
In this article, a method for landslides identification based on polarimetric decomposition techniques and the Wishart classifier is presented. Several parameters of Cloude decomposition and Freeman–Durden decomposition are introduced to analyse the radar scattering mechanisms over landslides and their surroundings.
Shiyu Luo, Ling Tong, Yan Chen, Longfei Tan   +3 more
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Full polarimetric GPR data decomposition and imaging

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016
Polarization is a property of electromagnetic wave that generally refers to the orientation of the electric field vector, which can be used to characterize target properties by polarimetric radar. Polarimetric decomposition methods have been common in the terrain and land-use classification based on plolarimetric synthetic aperture radar data. However,
Xuan Feng, Enhedelihai Nilot, Minghe Zhang, Shuaishuai Liang   +3 more
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PDFL: Polarimetric Decomposition Feature Learning via Deep Autoencoder

IEEE Transactions on Geoscience and Remote Sensing, 2022
Model-based polarimetric target decomposition (TD) generally solves scattering components and parameters under a preset decomposition base; then, decomposition features are also obtained. However, a preset base could not be adjusted according to different scenes. Furthermore, solving the polarimetric parameters needs exploring additional information or
Yang, Chen, Hou, Biao, Wu, Qian, Ren, Bo, Chanussot, Jocelyn, Wang, Shuang, Jiao, Licheng   +6 more
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Coherent Decomposition of Fully Polarimetric Radar Data

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008
This paper presents a coherent decomposition scheme for a few scattering matrix data. A simple model-fitting decomposition method is applied to retrieve scattering mechanism or identify scatterers based on the coherency matrix. The decomposition results are compared with some experimental data obtained by fully polarimetric FM-CW radar. It is shown the
Yoshio Yamaguchi, Jun Nakamura, Kazuyasu Aoyama, Hiroyoshi Yamada   +3 more
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