Results 31 to 40 of about 621 (141)

PolSAR Ship Detection Based on a SIFT-like PolSAR Keypoint Detector

Remote Sensing, 2022
The detection of ships on the open sea is an important issue for both military and civilian fields. As an active microwave imaging sensor, synthetic aperture radar (SAR) is a useful device in marine supervision.
Mingfei Gu, Yinghua Wang, Hongwei Liu, Penghui Wang   +3 more
doaj   +1 more source

PolSAR Image Modulation Using a Flexible Metasurface with Independently Controllable Polarizations

Remote Sensing
Recent advances in time-modulated metasurfaces (TMMs) have introduced approaches for controlling target features in radar imaging. These technologies enable dynamic reconstruction of scattering center locations and intensities by flexibly manipulating ...
Yuehan Wu, Junjie Wang, Jiong Wu, Guang Sun, Dejun Feng   +4 more
doaj   +1 more source

Polarimetric SAR cross-calibration method based on stable distributed targets

Geo-spatial Information Science
Polarimetric calibration is essential for the pre-processing of Polarimetric Synthetic Aperture Radar (PolSAR) data because it effectively mitigates polarimetric distortions in the measured PolSAR data.
Yongsheng Zhou, Peiyun Chen, Qiang Yin, Erxue Chen, Laurent Ferro-Famil, Fan Zhang   +5 more
doaj   +1 more source

Context-Based Max-Margin for PolSAR Image Classification

IEEE Access, 2017
Context-based method for classification has been successfully applied in image. However, most of these classifiers work in stages. This paper presents a novel discriminative model named context-based max-margin to perform the task of classification for ...
Shuyin Zhang, Biao Hou, Licheng Jiao, Qian Wu, Chen Sun, Wen Xie   +5 more
doaj   +1 more source

Interlinked Dynamics of Rice Cultivation Intensity and Ground Subsidence: Spatio‐Temporal Insights Into Water Resource Implications From Multi‐Year Spaceborne SAR Analysis

Water Resources Research, Volume 62, Issue 4, April 2026.
Abstract Sustainable rice cultivation is vital to meet global food demands, particularly in regions relying on groundwater for irrigation. Over‐pumping, however, can cause significant ground subsidence, threatening both infrastructure and agricultural sustainability.
Ya‐Lun S. Tsai, Xun‐Yan Liu
wiley   +1 more source

Error Source Analysis and Correction of GF-3 Polarimetric Data

Remote Sensing, 2018
The GaoFen-3 (GF-3) satellite is the first polarimetric synthetic aperture radar (PolSAR) satellite in China. With a designed in-orbit life of 8 years, it will provide large amounts of PolSAR data for ocean monitoring, disaster reduction, and many other ...
Sha Jiang, Xiaolan Qiu, Bing Han, Jili Sun, Chibiao Ding   +4 more
doaj   +1 more source

Unsupervised Cross-Domain Polarimetric Synthetic Aperture Radar (PolSAR) Change Monitoring Based on Limited-Label Transfer Learning and Vision Transformer

Remote Sensing
Limited labels and detailed changed land-cover interpretation requirements pose challenges for time-series PolSAR change monitoring research. Accurate labels and supervised models are difficult to reuse between massive unlabeled time-series PolSAR data due to the complex distribution shifts caused by different imaging parameters, scene changes, and ...
Xinyue Zhang, Rong Gui, Jun Hu, Jinghui Zhang, Lihuan Tan, Xixi Zhang   +5 more
openaire   +2 more sources

A Box Gradient‐Based Anisotropic Diffusion Framework for Polarimetric SAR Despeckling

Electronics Letters, Volume 62, Issue 1, January/December 2026.
This paper proposes a novel anisotropic diffusion framework for PolSAR despeckling, driven by a newly defined complex‐domain Box gradient. The method adaptively suppresses speckle while preserving structural and point‐target details, and experiments on real AIRSAR data confirm superior performance over existing filters.
Songli Han, Dawei Ren, Jian Yang
wiley   +1 more source

Exploring Polarimetric Properties Preservation for PolSAR Image Reconstruction With Complex‐Valued Convolutional Neural Networks

IET Radar, Sonar &Navigation, Volume 20, Issue 1, January/December 2026.
Polarimetric SAR data's inherent complex‐valued nature demands algorithms that work directly with complex representations, yet most deep‐learning approaches sidestep this by converting to the real domain. We implement and evaluate complex‐valued convolutional autoencoders that compress and accurately reconstruct full‐polarimetric SAR signals—preserving
Quentin Gabot, Joana Frontera‐Pons, Jérémy Fix, Chengfang Ren, Jean‐Philippe Ovarlez   +4 more
wiley   +1 more source

Machine learning classification based on k-Nearest Neighbors for PolSAR data

Anais da Academia Brasileira de Ciências
In this work, we focus on obtaining insights of the performances of some well-known machine learning image classification techniques (k-NN, Support Vector Machine, randomized decision tree and one based on stochastic distances) for PolSAR (Polarimetric ...
JODAVID A. FERREIRA, ANNY K.G. RODRIGUES, RAYDONAL OSPINA, LUIS GOMEZ   +3 more
doaj   +1 more source