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
Segmentation and Classification of Polarimetric SAR Data based on the KummerU Distribution [PDF]
, 2009 International audienceThinner spatial features can be observed from the high resolution of newly available spaceborne and airborne SAR images. Heterogeneous clutter models should be used to model the covariance matrix because each resolution cell ...
Bombrun, Lionel +5 more
core +3 more sources
SEL-Net: A Self-Supervised Learning-Based Network for PolSAR Image Runway Region Detection [PDF]
, 2023 Ping Han +4 more
openalex +1 more source
Remote Sensing, 2018 The mean shift algorithm has been shown to perform well in optical image segmentation. However, the conventional mean shift algorithm performs poorly if it is directly used with Synthetic Aperture Radar (SAR) images due to the large dynamic range and ...
Fengkai Lang +3 more
doaj +1 more source
Unsupervised classification of multilook polarimetric SAR data using spatially variant wishart mixture model with double constraints [PDF]
, 2018 This paper addresses the unsupervised classification problems for multilook Polarimetric synthetic aperture radar (PolSAR) images by proposing a patch-level spatially variant Wishart mixture model (SVWMM) with double constraints.
Fu, Kun +4 more
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
Semi-supervised classification of polarimetric SAR images using Markov random field and two-level Wishart mixture model [PDF]
, 2019 In this work, we propose a semi-supervised method for classification of polarimetric synthetic aperture radar (PolSAR) images. In the proposed method, a 2-level mixture model is constructed by associating each component density with a unique Wishart ...
Li, Heng-Chao +4 more
core +1 more source
Representative Learning via Span-Based Mutual Information for PolSAR Image Classification [PDF]
, 2021 Jianlong Wang +3 more
openalex +1 more source
Fully Polarimetric SAR Image Filtering by Combining Block Matching and Lee Filter
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingSpeckle filtering is a key preprocessing approach for the applications of polarimetric synthetic aperture radar (PolSAR) data. Most current PolSAR filtering algorithms can hardly get good balance in suppressing speckle and retaining image details.
Guisheng Zhao, Shengyuan Zhu, Yinglei Wu
doaj +1 more source
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