Results 91 to 100 of about 2,397 (207)
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 +3 more
doaj +1 more source
Earth and Space Science, Volume 11, Issue 4, April 2024.Abstract Many communities coexist with wildfires that lead to loss of lives, property, and ecosystem services. Remote sensing tools can aid disaster response and post‐event assessment, offering fire agencies opportunities for additional surveillance with radar, an all‐weather instrument that can image day or night.
Karen An, Cathleen E. Jones, Yunling Lou
wiley +1 more source
Statistical assessment of eigenvector-based target decomposition theorems in radar polarimetry [PDF]
, 2005 © 2005 IEEE.Carlos López-Martínez, Eric Pottier and Shane R ...
Cloude, Shane Robert +2 more
core +2 more sources
Graph Convolutional Networks by Architecture Search for PolSAR Image Classification [PDF]
, 2021 Hongying Liu +6 more
openalex +1 more source
IET Radar, Sonar &Navigation, Volume 18, Issue 3, Page 379-409, March 2024.The designed SSELF can automatically extract PolSAR features conducive to PolSAR image classification with a small number of training samples. Also, the designed deep learning model can obtain the effective features of homogeneous samples gathering together and heterogeneous samples separating from each other in a self‐supervised manner.
Mohsen Darvishnezhad, Mohammad Ali Sebt
wiley +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 +3 more
core +4 more sources
Earth and Space Science, Volume 11, Issue 1, January 2024.Abstract The potential of single date fully Polarimetric RADARSAT‐2 data in retrieving crop biophysical parameters using Machine Learning techniques was investigated. Various polarimetric parameters along with coherent and incoherent decomposition techniques were assessed for its sensitivity toward crop parameters like Wet and Dry Biomass, Crop Height,
Dharanya Thulasiraman +4 more
wiley +1 more source
Iterative Bilateral Filtering of Polarimetric SAR Data
, 2013 In this paper, we introduce an iterative speckle filtering method for polarimetric SAR (PolSAR) images based on the bilateral filter. To locally adapt to the spatial structure of images, this filter relies on pixel similarities in both spatial and ...
D'Hondt, Olivier +2 more
core +1 more source
Degree of Polarization-Based Data Filter for Fully Polarimetric Synthetic Aperture Radar [PDF]
, 2019 This paper proposes a novel data filtering algorithm for fully polarimetric synthetic aperture radar (PolSAR) based on the degree of polarization (DoP) information.
Akira Hirose, Fang Shang, Naoto Kishi
core +2 more sources
Nonlinear Manifold Learning Integrated with Fully Convolutional Networks for PolSAR Image Classification [PDF]
, 2020 Chu He +3 more
openalex +1 more source