Results 61 to 70 of about 2,421 (185)

Investigation of the capability of multitemporal RADARSAT-2 fully polarimetric SAR images for land cover classification: a case of Panyu, Guangdong province

European Journal of Remote Sensing, 2021
Synthetic aperture radar (SAR), with all-day and all-weather observation capabilities, can capture the phenology of crops with short growth cycles to improve land cover classification results.
Di Liu, Zhixin Qi, Hui Zhang, Xia Li, Anthony Gar-on Yeh, Jiao Wang   +5 more
doaj   +1 more source

Training Sample Selection Based on SAR Images Quality Evaluation With Multi‐Indicators Fusion

IET Signal Processing, Volume 2025, Issue 1, 2025.
In recent years, with the development of artificial neural networks, efficiently training models for synthetic aperture radar (SAR) image classification tasks has garnered significant attention from researchers. Particularly when dealing with datasets containing a large number of redundant samples, the selection of training samples becomes crucial for ...
Pengcheng Wang, Huanyu Liu, Junbao Li, Hasan Mir   +3 more
wiley   +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, De, Shaunak, Frery, Alejandro C., Manickam, Surendar, Muhuri, Arnab   +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, Gay, Michel, Totir, Felix, Vasile, Gabriel   +3 more
core   +4 more sources

Consistency Regularization Semisupervised Learning for PolSAR Image Classification

International Journal of Intelligent Systems, Volume 2025, Issue 1, 2025.
Polarimetric Synthetic Aperture Radar (PolSAR) images have emerged as an important data source for land cover classification research due to their all‐weather, all‐day monitoring capabilities. Deep learning‐based classification methods have recently gained significant attention in PolSAR image classification since they have demonstrated excellent ...
Yu Wang, Shan Jiang, Weijie Li, Mohamadreza (Mohammad) Khosravi   +3 more
wiley   +1 more source

Improvement of PolSAR Decomposition Scattering Powers Using a Relative Decorrelation Measure

, 2017
In this letter, a methodology is proposed to improve the scattering powers obtained from model-based decomposition using Polarimetric Synthetic Aperture Radar (PolSAR) data.
Bhattacharya, A., Ratha, D., Surendar, M.   +2 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, 24435, 24436, 24437, Hirose, Akira, Kinugawa, Kazutaka, Shang, Fang, Usami, Naoto   +7 more
core   +2 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, K. Elder, D. McGrath, H. P. Marshall, B. Starr, N. Adebisi, R. T. Palomaki, Z. Hoppinen   +7 more
wiley   +1 more source

Bias Correction and Modified Profile Likelihood under the Wishart Complex Distribution

, 2014
This paper proposes improved methods for the maximum likelihood (ML) estimation of the equivalent number of looks $L$. This parameter has a meaningful interpretation in the context of polarimetric synthetic aperture radar (PolSAR) images.
Cintra, Renato J., Frery, Alejandro C., Nascimento, Abraão D. C.   +2 more
core   +1 more source

An optimised scattering power decomposition method oriented to ship detection in polarimetric synthetic aperture radar imagery

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