Results 71 to 80 of about 13,122,784 (192)

Unsupervised Classification for Polarimetric Synthetic Aperture Radar Images Based on Wishart Mixture Models

Leida xuebao, 2017
Unsupervised classification is a significant step inthe automated interpretation of Polarimetric Synthetic Aperture Radar (PolSAR) images. However, determining the number of clusters in this process is still a challenging problem. To this end, we propose
Zhong Neng, Yang Wen, Yang Xiangli, Guo Wei   +3 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

The Improved Three-Step Semi-Empirical Radiometric Terrain Correction Approach for Supervised Classification of PolSAR Data

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, Erxue Chen, Zengyuan Li, Yaxiong Fan, Kunpeng Xu   +4 more
doaj   +1 more source

Classification for Polsar image based on hölder divergences [PDF]

The Journal of Engineering, 2019
(Dis)similarity measures play an important role in the interpretation of polarimetric synthetic aperture radar (PolSAR) images. Here, the authors introduce a kind of similarity measures for PolSAR images based on the concepts of Hölder pseudo‐divergence and Hölder divergence.
Ting Pan, Dong Peng, Xiangli Yang, Pingping Huang, Wen Yang   +4 more
openaire   +2 more sources

PolSAR Image Classification Based on Robust Low-Rank Feature Extraction and Markov Random Field [PDF]

, 2022
Polarimetric synthetic aperture radar (PolSAR) image classification has been investigated vigorously in various remote sensing applications. However, it is still a challenging task nowadays.
Hong, Danfeng, Wei, Zhiqiang, Yao, Jing, Chanussot, Jocelyn, Bi, Haixia, Danfeng Hong, Jocelyn Chanussot, Jing Yao, Zhiqiang Wei, Haixia Bi   +9 more
core   +1 more source

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

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

A novel semicoupled projective dictionary pair learning method for PolSAR image classification

, 2019
Polarimetric synthetic aperture radar (PolSAR) image classification plays an important role in remote sensing image processing. In recent years, stacked auto-encoder (SAE) has obtained a series of excellent results in PolSAR image classification.
Chen, Yanqiao, Jiao, Licheng, Li, Yangyang, Ren, Bo, Marturi, Naresh, Zhang, Dan, Li, Lingling   +6 more
core   +1 more source

Semi-supervised PolSAR Image Classification Based on the Neighborhood Minimum Spanning Tree

Leida xuebao, 2019
In this paper, a novel semi-supervised classification method based on the Neighborhood Minimum Spanning Tree (NMST) is proposed to solve the Polarimetric Synthetic Aperture Radar (PolSAR) terrain classification when labeled samples are few. Combining the
HUA Wenqiang, WANG Shuang, GUO Yanhe, XIE Wen   +3 more
doaj   +1 more source

Ground moving target indication of polarimetric interferometric synthetic aperture radar using joint scattering vector

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, Long Cheng, Chunhui Yu, Shiwei Zhang   +3 more
wiley   +1 more source