Classification with a non-Gaussian model for PolSAR data
In this paper, we present a generalized Wishart classifier derived from a non-Gaussian
model for polarimetric synthetic aperture radar (PolSAR) data. Our starting point is to …
model for polarimetric synthetic aperture radar (PolSAR) data. Our starting point is to …
A fusion approach to retrieve soil moisture with SAR and optical data
The retrieval of soil moisture in vegetated areas with active microwave remote sensing is a
challenging process because scattering form the vegetated area incorporates the volume …
challenging process because scattering form the vegetated area incorporates the volume …
Multiyear crop monitoring using polarimetric RADARSAT-2 data
C Liu, J Shang, PW Vachon… - IEEE Transactions on …, 2012 - ieeexplore.ieee.org
This paper studies the feasibility of monitoring crop growth based on a trend analysis of
three elementary radar scattering mechanisms using three consecutive years (2008–2010) …
three elementary radar scattering mechanisms using three consecutive years (2008–2010) …
Analytic expressions for stochastic distances between relaxed complex Wishart distributions
The scaled complex Wishart distribution is a widely used model for multilook full polarimetric
synthetic aperture radar data whose adequacy is attested in this paper. Classification …
synthetic aperture radar data whose adequacy is attested in this paper. Classification …
Land cover classification of PALSAR images by knowledge based decision tree classifier and supervised classifiers based on SAR observables
P Mishra, D Singh, Y Yamaguchi - Progress In Electromagnetics Research …, 2011 - jpier.org
The intent of this paper is to explore the application of information obtained from fully
polarimetric data for land cover classification. Various land cover classification techniques …
polarimetric data for land cover classification. Various land cover classification techniques …
PolSAR image classification with lightweight 3D convolutional networks
H Dong, L Zhang, B Zou - Remote Sensing, 2020 - mdpi.com
Convolutional neural networks (CNNs) have become the state-of-the-art in optical image
processing. Recently, CNNs have been used in polarimetric synthetic aperture radar …
processing. Recently, CNNs have been used in polarimetric synthetic aperture radar …
[PDF][PDF] Classification of polarimetric SAR image based on support vector machine using multiple-component scattering model and texture features
L Zhang, B Zou, J Zhang, Y Zhang - EURASIP Journal on Advances in …, 2009 - Springer
The classification of polarimetric SAR image based on Multiple-Component Scattering
Model (MCSM) and Support Vector Machine (SVM) is presented in this paper. MCSM is a …
Model (MCSM) and Support Vector Machine (SVM) is presented in this paper. MCSM is a …
A statistical-measure-based adaptive land cover classification algorithm by efficient utilization of polarimetric SAR observables
P Mishra, D Singh - IEEE Transactions on Geoscience and …, 2013 - ieeexplore.ieee.org
The polarimetric information contained in polarimetric synthetic aperture radar (SAR) images
represents great potential for characterization of natural and urban surfaces. However, it is …
represents great potential for characterization of natural and urban surfaces. However, it is …
Land cover classification for polarimetric SAR images based on mixture models
W Gao, J Yang, W Ma - Remote Sensing, 2014 - mdpi.com
In this paper, two mixture models are proposed for modeling heterogeneous regions in
single-look and multi-look polarimetric SAR images, along with their corresponding …
single-look and multi-look polarimetric SAR images, along with their corresponding …
[PDF][PDF] Scale mixture of Gaussian modelling of polarimetric SAR data
This paper describes a flexible non-Gaussian statistical method used to model polarimetric
synthetic aperture radar (POLSAR) data. We outline the theoretical basis of the well-know …
synthetic aperture radar (POLSAR) data. We outline the theoretical basis of the well-know …