Results 61 to 70 of about 3,590 (264)
An Unsupervised PolSAR Image Classification Algorithm Based on Tensor Product Graph Diffusion
Leida xuebao, 2019 To overcome the difficulty of similarity expression and the effects of speckle noise in unsupervised classification of Polarimetric Synthetic Aperture Radar (PolSAR) images, a novel unsupervised PolSAR image terrain classification algorithm based on ...
ZOU Huanxin +5 more
doaj +1 more source
Modifying the Yamaguchi Four-Component Decomposition Scattering Powers Using a Stochastic Distance
, 2015 Model-based decompositions have gained considerable attention after the initial work of Freeman and Durden. This decomposition which assumes the target to be reflection symmetric was later relaxed in the Yamaguchi et al.
Bhattacharya, Avik +4 more
core +1 more source
Hierarchical Segmentation of Polarimetric SAR Images Using Heterogeneous Clutter Models [PDF]
, 2011 International audienceIn this paper, heterogeneous clutter models are used to describe polarimetric synthetic aperture radar (PolSAR) data. The KummerU distribution is introduced to model the PolSAR clutter.
Bombrun, Lionel +3 more
core +4 more sources
L‐Band InSAR Snow Water Equivalent Retrieval Uncertainty Increases With Forest Cover Fraction
Geophysical Research Letters, Volume 51, Issue 24, 28 December 2024.Abstract There is a pressing need for global monitoring of snow water equivalent (SWE) at high spatiotemporal resolution, and L‐band (1–2 GHz) interferometric synthetic aperture radar (InSAR) holds promise. However, the technique has not seen extensive evaluation in forests.
R. Bonnell +7 more
wiley +1 more source
, 2013 A new classifier for Polarimetric SAR (PolSAR) images is proposed and assessed in this paper. Its input consists of segments, and each one is assigned the class which minimizes a stochastic distance. Assuming the complex Wishart model, several stochastic
da Silva, Wagner Barreto +3 more
core +1 more source
Isotropization of Quaternion-Neural-Network-Based PolSAR Adaptive Land Classification in Poincare-Sphere Parameter Space [PDF]
, 2018 Quaternion neural networks (QNNs) achieve high accuracy in polarimetric synthetic aperture radar classification for various observation data by working in Poincare-sphere-parameter space.
24434 +7 more
core +2 more sources
IET Radar, Sonar &Navigation, Volume 18, Issue 12, Page 2642-2656, December 2024.An optimised scattering power decomposition model is proposed which comprises surface, double‐bounce, oriented dipole and volume scattering components. The authors derive the optimised four‐component decomposition model from mathematical and theoretical perspectives, and verify the rationality of the optimised decomposition model using large amounts of
Lu Fang, Wenxing Mu, Ning Wang, Tao Liu
wiley +1 more source
PSRN: Polarimetric Space Reconstruction Network for PolSAR Image Semantic Segmentation [PDF]
, 2021 Hao Jing +4 more
openalex +1 more source
IET Radar, Sonar &Navigation, Volume 18, Issue 12, Page 2681-2697, December 2024.SAR GMTI is of great importance for both civlisation and military applications. The clutter suppression performance is an important assurance for the accuracy and precision of GMTI. To achieve better clutter suppression performance, it often requires extremely precise registration of multi‐channel data, including polarization and interferometric ...
Jing Xu +3 more
wiley +1 more source
Prototype Theory Based Feature Representation for PolSAR Images
Leida xuebao, 2016 This study presents a new feature representation approach for Polarimetric Synthetic Aperture Radar (PolSAR) image based on prototype theory. First, multiple prototype sets are generated using prototype theory.
Huang Xiaojing +3 more
doaj +1 more source