Results 61 to 70 of about 2,377 (186)
Deep learning in remote sensing: a review [PDF]
, 2017 Standing at the paradigm shift towards data-intensive science, machine learning techniques are becoming increasingly important. In particular, as a major breakthrough in the field, deep learning has proven as an extremely powerful tool in many fields ...
Fraundorfer, Friedrich +6 more
core +4 more sources
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
Machine learning classification based on k-Nearest Neighbors for PolSAR data
Anais da Academia Brasileira de CiênciasIn 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 +3 more
doaj +1 more source
IEEE Access, 2018 Numerous radar polarimetry theories and polarimetric synthetic aperture radar (PolSAR) processing methods have been developed. However, the vast majority of SAR images are not fully polarimetric (full-pol).
Qian Song, Feng Xu, Ya-Qiu Jin
doaj +1 more source
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 +3 more
wiley +1 more source
IET Radar, Sonar &Navigation, Volume 18, Issue 10, Page 1919-1936, October 2024.The authors propose a novel waveform, namely, the orthogonal double V‐linear frequency modulation (ODV‐LFM) and corresponding simultaneous polarimetric measurement and pointwise linear and non‐linear processing methods. The proposed waveform can mitigate the influence of delay‐Doppler coupling and reduce the risk of false targets and ghosts in multiple‐
Biao Shen +3 more
wiley +1 more source
IET Radar, Sonar &Navigation, Volume 18, Issue 7, Page 1106-1115, July 2024.The manuscript mainly investigates the sparse distributed vegetation height inversion problem. By analysing the scattering mechanisms of the sparse distributed vegetation, the authors proposed a method to select the samples to estimate PolInSAR coherence and vegetation height in non‐local areas by using the amplitude‐normalised interferometric phase ...
Jing Xu +3 more
wiley +1 more source
Discussion on Application of Polarimetric Synthetic Aperture Radar in Marine Surveillance
Leida xuebao, 2016 Synthetic Aperture Radar (SAR), an important earth observation sensor, has been used in a wide range of applications for land and marine surveillance. Polarimetric SAR (PolSAR) can obtain abundant scattering information of a target to improve the ability
Zhang Jie +3 more
doaj +1 more source
Entropy-based Statistical Analysis of PolSAR Data
, 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 +1 more source
3-D glacier subsurface characterization using SAR polarimetry [PDF]
, 2015 The paper introduces a new polarimetric scattering model able to interpret and invert coherent polarimetric SAR (PolSAR) measurements over glaciers and ice sheets.
Hajnsek, Irena +2 more
core +1 more source