Results 21 to 30 of about 505 (177)

Convolutional Kernel‐based covariance descriptor for classification of polarimetric synthetic aperture radar images

open access: yesIET Radar, Sonar & Navigation, 2022
There are two types of important information in a polarimetric synthetic aperture radar (PolSAR) image: spatial features in two dimensions and polarimetric characteristics in the scattering dimension. Considering both polarimetric and spatial information
Maryam Imani
doaj   +1 more source

A new clustering algorithm for PolSAR images segmentation [PDF]

open access: yes2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2019
This paper deals with polarimetric synthetic aperture radar (PolSAR) image segmentation. More precisely, we present a new robust clustering algorithm designed for non-Gaussian data. The algorithm is based on an expectation-maximization approach. Its novelty is that, in addition to the estimation of each cluster center and covariance matrix, it also ...
Violeta Roizman   +2 more
openaire   +1 more source

Classification of Polarimetric SAR Images Based on the Riemannian Manifold

open access: yesLeida xuebao, 2017
Classification is one of the core components in the interpretation of Polarimetric Synthetic Aperture Radar (PolSAR) images. A new PolSAR image classification approach employs the structural properties of the Riemannian manifold formed by PolSAR ...
Yang Wen   +3 more
doaj   +1 more source

A Novel Multi-Feature Joint Learning Method for Fast Polarimetric SAR Terrain Classification

open access: yesIEEE Access, 2020
Polarimetric synthetic aperture radar (PolSAR) image classification is one of the most important study areas for PolSAR image processing. Many kinds of PolSAR features can be extracted for PolSAR image classification, such as the scattering, polarimetric
Junfei Shi, Haiyan Jin, Xiaohua Li
doaj   +1 more source

Superpixel-Oriented Unsupervised Classification for Polarimetric SAR Images Based on Consensus Similarity Network Fusion

open access: yesIEEE Access, 2019
Unsupervised polarimetric synthetic aperture radar (PolSAR) image classification is an important task in PolSAR automatic image analysis and interpretation.
Huanxin Zou   +3 more
doaj   +1 more source

Adversarial Reconstruction-Classification Networks for PolSAR Image Classification

open access: yesRemote Sensing, 2019
Polarimetric synthetic aperture radar (PolSAR) image classification has become more and more widely used in recent years. It is well known that PolSAR image classification is a dense prediction problem. The recently proposed fully convolutional networks (
Yanqiao Chen   +5 more
doaj   +1 more source

Polarimetric Convolutional Network for PolSAR Image Classification [PDF]

open access: yesIEEE Transactions on Geoscience and Remote Sensing, 2019
15 ...
Xu Liu 0006   +4 more
openaire   +4 more sources

POLSAR Image Classification via Clustering-WAE Classification Model

open access: yesIEEE Access, 2018
Considering the clustering algorithms could explore the label information automatically, this paper proposes a new method in terms of polarimetric synthetic aperture radar (POLSAR) image classification, which named a clustering-wishart-auto-encoder (WAE)
Wen Xie, Ziwei Xie, Feng Zhao, Bo Ren
doaj   +1 more source

A Novel Classification Method for PolSAR Image Combining the Deep Learning Model and Adaptive Boosting of Shallow Classifiers

open access: yesCanadian Journal of Remote Sensing, 2023
Polarimetric synthetic aperture radar (PolSAR) images are classified mainly according to the backscattering information of ground objects. For regions with complex backscattering information, misclassification is easy to occur, which leads to challenges ...
Yan Duan   +3 more
doaj   +1 more source

PolSAR Image Feature Extraction via Co-Regularized Graph Embedding

open access: yesRemote Sensing, 2020
Dimensionality reduction (DR) methods based on graph embedding are widely used for feature extraction. For these methods, the weighted graph plays a vital role in the process of DR because it can characterize the data’s structure information.
Xiayuan Huang, Xiangli Nie, Hong Qiao
doaj   +1 more source

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