Results 11 to 20 of about 2,015 (220)

Consistency Regularization Semisupervised Learning for PolSAR Image Classification

International Journal of Intelligent Systems
Polarimetric Synthetic Aperture Radar (PolSAR) images have emerged as an important data source for land cover classification research due to their all‐weather, all‐day monitoring capabilities. Deep learning‐based classification methods have recently gained significant attention in PolSAR image classification since they have demonstrated excellent ...
Yu Wang, Shan Jiang, Weijie Li
openaire   +2 more sources

A New Parallel Dual-Channel Fully Convolutional Network Via Semi-Supervised FCM for PolSAR Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Convolutional neural network (CNN) has achieved remarkable success in polarimetric synthetic aperture radar (PolSAR) image classification. However, the PolSAR image classification is a pixelwise prediction assignment.
Feng Zhao, Min Tian, Wen Xie, Hanqiang Liu   +3 more
doaj   +1 more source

Joint Polarimetric-Adjacent Features Based on LCSR for PolSAR Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Image classification is a critical and important application in PolSAR image interpretation. Finding a feature extraction method, which can effectively describe the characteristics of the target, is an important basis for image classification.
Xiao Wang, Lamei Zhang, Ning Wang, Bin Zou   +3 more
doaj   +1 more source

Polarimetric Decomposition and Machine Learning‐Based Classification of L‐ and S‐Band Airborne SAR (LS‐ASAR) Data

Earth and Space Science, Volume 10, Issue 6, June 2023., 2023
Abstract The polarimetric Synthetic Aperture Radar (SAR) data sets have been widely exploited for land use land cover (LULC) classification due to their sensitivity to the structural and dielectric properties of the imaging target. In this study, the potential of fully polarimetric L‐ and S‐band Airborne SAR (LS‐ASAR) data sets were explored for the ...
Shatakshi Verma, Shashi Kumar, Hamish Dsouza   +2 more
wiley   +1 more source

PolSAR Image Land Cover Classification Based on Hierarchical Capsule Network

Remote Sensing, 2021
Polarimetric synthetic aperture radar (PolSAR) image classification is one of the basic methods of PolSAR image interpretation. Deep learning algorithms, especially convolutional neural networks (CNNs), have been widely used in PolSAR image ...
Jianda Cheng, Fan Zhang, Deliang Xiang, Qiang Yin, Yongsheng Zhou, Wei Wang   +5 more
doaj   +1 more source

Feature fusion method based on local binary graph for PolSAR image classification

IET Radar, Sonar &Navigation, Volume 17, Issue 6, Page 939-954, June 2023., 2023
We propose a novel supervised version of GCNs named mini‐GCNs, for short. As the name suggests, mini‐GCNs can be trained in mini‐batch fashion, trying to achieve a better and more robust local optimum. To remove the redundant information extracted from the designed CNN and mini‐GCN, a feature fusion method is proposed to achieve better classification ...
Mohammad Ali Sebt, Mohsen Darvishnezhad
wiley   +1 more source

Polarimetric Convolutional Network for PolSAR Image Classification [PDF]

IEEE Transactions on Geoscience and Remote Sensing, 2019
15 ...
Xu Liu, Licheng Jiao, Xu Tang, Qigong Sun, Dan Zhang   +4 more
openaire   +2 more sources

Permafrost Dynamics Observatory (PDO): 2. Joint Retrieval of Permafrost Active Layer Thickness and Soil Moisture From L‐Band InSAR and P‐Band PolSAR

Earth and Space Science, Volume 10, Issue 1, January 2023., 2023
Abstract Seasonal subsidence induced by ground ice melt can be measured by interferometric synthetic aperture radar (InSAR) techniques to infer active layer thickness (ALT) in permafrost regions. The magnitude of subsidence depends on both how deep the soil thawed and how much ice/water content existed in the active layer soil.
Richard H. Chen, Roger J. Michaelides, Yuhuan Zhao, Lingcao Huang, Elizabeth Wig, Taylor D. Sullivan, Andrew D. Parsekian, Howard A. Zebker, Mahta Moghaddam, Kevin M. Schaefer   +9 more
wiley   +1 more source

PolSAR Image Classification via Learned Superpixels and QCNN Integrating Color Features

Remote Sensing, 2019
Polarimetric synthetic aperture radar (PolSAR) image classification plays an important role in various PolSAR image application. And many pixel-wise, region-based classification methods have been proposed for PolSAR images.
Xinzheng Zhang, Jili Xia, Xiaoheng Tan, Xichuan Zhou, Tao Wang   +4 more
doaj   +1 more source

Polarimetric SAR image classification using binary coding‐based polarimetric‐morphological features

IET Image Processing, Volume 16, Issue 14, Page 3715-3736, 11 December 2022., 2022
Abstract Polarimetric synthetic aperture radar (POLSAR) systems provide high resolution images containing polarimetric information. So, they have high capability in land cover classification. In this work, a binary coding‐based polarimetric‐morphological (BCPM) feature extraction is proposed for POLSAR image classification.
Maryam Imani
wiley   +1 more source