Segmentation of multi-temporal polarimetric SAR data based on mean-shift and spectral graph partitioning [PDF]
PeerJ, 2022 Polarimetric SAR (PolSAR) image segmentation is a key step in its interpretation. For the targets with time series changes, the single-temporal PolSAR image segmentation algorithm is difficult to provide correct segmentation results for its target ...
Caiqiong Wang +4 more
doaj +3 more sources
Entropy-based Statistical Analysis of PolSAR Data [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2012 Images obtained from coherent illumination processes are contaminated with speckle noise, with polarimetric synthetic aperture radar (PolSAR) imagery as a prominent example.
Cintra, Renato J. +2 more
core +3 more sources
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 +3 more
doaj +2 more sources
A Novel Change Detection Method Based on Statistical Distribution Characteristics Using Multi-Temporal PolSAR Data [PDF]
Sensors, 2020 Unsupervised change detection approaches, which are relatively straightforward and easy to implement and interpret, and which require no human intervention, are widely used in change detection. Polarimetric synthetic aperture radar (PolSAR), which has an
Jinqi Zhao +5 more
doaj +2 more sources
AIR-PolSAR-Seg: A Large-Scale Data Set for Terrain Segmentation in Complex-Scene PolSAR Images
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Polarimetric synthetic aperture radar (PolSAR) terrain segmentation is a fundamental research topic in PolSAR image interpretation. Recently, many studies have been investigated to handle this task.
Zhirui Wang +4 more
doaj +2 more sources
PolSAR-SFCGN: An End-to-End PolSAR Superpixel Fully Convolutional Generation Network
Remote SensingPolarimetric Synthetic Aperture Radar (PolSAR) image classification is one of the most important applications in remote sensing. The impressive superpixel generation approaches can improve the efficiency of the subsequent classification task and restrain
Mengxuan Zhang +6 more
doaj +2 more sources
A Review on PolSAR Decompositions for Feature Extraction. [PDF]
J ImagingFeature extraction plays a pivotal role in processing remote sensing datasets, especially in the realm of fully polarimetric data. This review investigates a variety of polarimetric decomposition techniques aimed at extracting comprehensive information from polarimetric imagery.
Karachristos K +2 more
europepmc +4 more sources
Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks [PDF]
Sensors, 2018 Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image ...
Lei Wang +4 more
doaj +2 more sources
A Quality Assessment Method Based on Common Distributed Targets for GF-3 Polarimetric SAR Data [PDF]
Sensors, 2018 The GaoFen-3 (GF-3) satellite, launched on 10 August 2016, is the first C-band polarimetric synthetic aperture radar (PolSAR) satellite in China. The PolSAR system of GF-3 can collect a significant wealth of information for geophysical research and ...
Sha Jiang +3 more
doaj +2 more sources
PolSAR Models with Multimodal Intensities
Remote Sensing, 2022 Polarimetric synthetic aperture radar (PolSAR) systems are an important remote sensing tool. Such systems can provide high spacial resolution images, but they are contaminated by an interference pattern called multidimensional speckle. This fact requires that PolSAR images receive specialised treatment; particularly, tailored models which are close to ...
Jodavid A. Ferreira +2 more
openaire +3 more sources