Results 21 to 30 of about 7,181 (241)
Turbo Speckle Filtering applied to PolSAR Data [PDF]
IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008 A new approach for speckle reduction in polarimetric synthetic aperture radar (PolSAR) images based on the turbo iterative principle is proposed. The turbo iterative algorithm shows high performances due to the propagation of the information between two complementary filters.
Farage, Grégory +3 more
openaire +2 more sources
Earth and Space Science, Volume 10, Issue 6, June 2023., 2023 Abstract The polarimetric Synthetic Aperture Radar (SAR) data sets have been widely exploited for land use land cover (LULC) classification due to their sensitivity to the structural and dielectric properties of the imaging target. In this study, the potential of fully polarimetric L‐ and S‐band Airborne SAR (LS‐ASAR) data sets were explored for the ...
Shatakshi Verma +2 more
wiley +1 more source
Feature fusion method based on local binary graph for PolSAR image classification
IET Radar, Sonar &Navigation, Volume 17, Issue 6, Page 939-954, June 2023., 2023 We propose a novel supervised version of GCNs named mini‐GCNs, for short. As the name suggests, mini‐GCNs can be trained in mini‐batch fashion, trying to achieve a better and more robust local optimum. To remove the redundant information extracted from the designed CNN and mini‐GCN, a feature fusion method is proposed to achieve better classification ...
Mohammad Ali Sebt, Mohsen Darvishnezhad
wiley +1 more source
Earth and Space Science, Volume 10, Issue 1, January 2023., 2023 Abstract Seasonal subsidence induced by ground ice melt can be measured by interferometric synthetic aperture radar (InSAR) techniques to infer active layer thickness (ALT) in permafrost regions. The magnitude of subsidence depends on both how deep the soil thawed and how much ice/water content existed in the active layer soil.
Richard H. Chen +9 more
wiley +1 more source
Remote Sensing, 2023 Recently, deep learning methods have been widely studied in the field of polarimetric synthetic aperture radar (PolSAR) ship detection. However, extracting polarimetric and spatial features on the whole PolSAR image will result in high computational ...
Weixing Qiu, Zongxu Pan
doaj +1 more source
Optimum graph cuts for pruning binary partition trees of polarimetric SAR images [PDF]
, 2016 This paper investigates several optimum graph-cut techniques for pruning binary partition trees (BPTs) and their usefulness for the low-level processing of polarimetric synthetic aperture radar (PolSAR) images.
Foucher, Samuel +1 more
core +2 more sources
Polarimetric SAR image classification using binary coding‐based polarimetric‐morphological features
IET Image Processing, Volume 16, Issue 14, Page 3715-3736, 11 December 2022., 2022 Abstract Polarimetric synthetic aperture radar (POLSAR) systems provide high resolution images containing polarimetric information. So, they have high capability in land cover classification. In this work, a binary coding‐based polarimetric‐morphological (BCPM) feature extraction is proposed for POLSAR image classification.
Maryam Imani
wiley +1 more source
IET Radar, Sonar &Navigation, Volume 16, Issue 12, Page 1924-1935, December 2022., 2022 Abstract In this paper, the terrain effect on parameter inversion performance of polarimetric synthetic aperture radar (PolSAR) and polarimetric SAR interferometry (PolInSAR) are analysed first. Based on the analysis of the terrain effect on single pixel processing, the terrain effect between adjacent pixels is addressed for both PolSAR and PolInSAR ...
Suo Zhiyong +3 more
wiley +1 more source
PolSAR-Decomposition-Based Extended Water Cloud Modeling for Forest Aboveground Biomass Estimation
Remote Sensing, 2019 Polarimetric synthetic aperture radar (PolSAR) remote sensing has been widely used for forest mapping and monitoring. PolSAR data has the capability to provide scattering information that is contributed by different scatterers within a single SAR ...
Shashi Kumar +3 more
doaj +1 more source
Supervised PolSAR Image Classification with Multiple Features and Locally Linear Embedding. [PDF]
Sensors (Basel), 2018 Zhang Q, Wei X, Xiang D, Sun M.
europepmc +3 more sources