Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks [PDF]
Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image ...
Lei Wang +4 more
doaj +5 more sources
Adversarial Reconstruction-Classification Networks for PolSAR Image Classification [PDF]
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 +4 more sources
PolSAR Image Classification Based on Relation Network with SWANet
Deep learning and convolutional neural networks (CNN) have been widely applied in polarimetric synthetic aperture radar (PolSAR) image classification, and satisfactory results have been obtained. However, there is one crucial issue that still has not been solved. These methods require abundant labeled samples and obtaining the labeled samples of PolSAR
Hua Wenqiang +2 more
exaly +4 more sources
Structure Label Matrix Completion for PolSAR Image Classification [PDF]
Terrain classification is a hot topic in polarimetric synthetic aperture radar (PolSAR) image interpretation that aims at assigning a label to every pixel and forms a label matrix for a PolSAR image.
Qian Wu +5 more
doaj +3 more sources
PolSAR Image Classification via Learned Superpixels and QCNN Integrating Color Features
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 +4 more
doaj +4 more sources
PolSAR Image Land Cover Classification Based on Hierarchical Capsule Network
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 +5 more
doaj +4 more sources
POLSAR Image Classification via Clustering-WAE Classification Model
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 +5 more sources
Deep learning can archive state-of-the-art performance in polarimetric synthetic aperture radar (PolSAR) image classification with plenty of labeled data.
Lei Wang +4 more
doaj +4 more sources
Two-step discriminant analysis based multi-view polarimetric SAR image classification with high confidence [PDF]
Polarimetric synthetic aperture radar (PolSAR) image classification is a hot topic in remote sensing field. Although recently many deep learning methods such as convolutional based networks have provided great success in PolSAR image classification, but ...
Maryam Imani
doaj +2 more sources
Unsupervised Classification of Polarimetric SAR Image Based on Geodesic Distance and Non-Gaussian Distribution Feature [PDF]
Polarimetric synthetic aperture radar (PolSAR) image classification plays a significant role in PolSAR image interpretation. This letter presents a novel unsupervised classification method for PolSAR images based on the geodesic distance and K-Wishart ...
Junrong Qu +3 more
doaj +2 more sources

