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A new method for classification of POLSAR images
2016 6th International Conference on Computer and Knowledge Engineering (ICCKE), 2016The present paper proposes an unsupervised feature learning method for POLSAR image classification. The proposed method includes two steps. In these two steps, features are created and learned from scratch. The first is to learn dictionaries and encode features using scatter matrices.
Nastaran Aghaei, Gholamreza Akbarizadeh
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Adaptive Graph Convolutional Network for PolSAR Image Classification
IEEE Transactions on Geoscience and Remote Sensing, 2022Polarimetric synthetic aperture radar (PolSAR) image classification is one of the hottest issues in remote sensing, where studies on pixel-level information and relationship are of great significance. In this article, graph convolutional network (GCN) is employed to accomplish this pixel-level task benefiting from its excellent capability in structure ...
Fang Liu +5 more
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Supervised Polsar Image Classification by Combining Multiple Features
2019 IEEE International Conference on Image Processing (ICIP), 2019For polarimetric synthetic aperture radar (PolSAR) image classification, each pixel can be represented by multiple features from different perspectives, such as polarimetric feature (PF), texture feature (TF) and color feature (CF). Both multi-view canonical correlation analysis (MCCA) and multi-view spectral embedding (MSE) are two unsupervised multi ...
Xiayuan Huang +3 more
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Robust Semisupervised Classification for PolSAR Image With Noisy Labels
IEEE Transactions on Geoscience and Remote Sensing, 2017The robustness of the supervised polarimetric synthetic aperture radar (PolSAR) image classification is severely affected by two main aspects, namely, the quantity and quality of the labeled training pixels. Specifically, limited manually labeled pixels with respect to the large scale of PolSAR image have limited the performance of the automatic ...
Biao Hou +3 more
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An Unsupervised Scattering Mechanism Classification Method for PolSAR Images
IEEE Geoscience and Remote Sensing Letters, 2014This letter concentrates on scattering mechanism classification of polarimetric synthetic aperture radar (PolSAR) images. Scattering mechanism classes are defined as the combinations of dominant and secondary scattering mechanisms. With three metrics extracted from the observed coherency matrix, an unsupervised classifier is proposed to classify PolSAR
Xiaoguang Cheng +2 more
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Unsupervised PolSAR Image Classification Using Discriminative Clustering
IEEE Transactions on Geoscience and Remote Sensing, 2017This paper presents a novel unsupervised image classification method for polarimetric synthetic aperture radar (PolSAR) data. The proposed method is based on a discriminative clustering framework that explicitly relies on a discriminative supervised classification technique to perform unsupervised clustering. To implement this idea, we design an energy
Haixia Bi, Jian Sun 0009, Zongben Xu
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Unsupervised PolSAR image classification based on ensemble partitioning
2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS, 2013This work introduces an unsupervised classification framework based on ensemble partitioning for polarimetric synthetic aperture radar (PolSAR) data, which can automatically determine the number of categories. First, the PolSAR image is divided into patches by an over-segmentation method.
Xiaoshuang Yin +4 more
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Task-Oriented GAN for PolSAR Image Classification and Clustering
IEEE Transactions on Neural Networks and Learning Systems, 2019Based on a generative adversarial network (GAN), a novel version named Task-Oriented GAN is proposed to tackle difficulties in PolSAR image interpretation, including PolSAR data analysis and small sample problem. Besides two typical parts in GAN, i.e., generator (G-Net) and discriminator (D-Net), there is a third part named TaskNet (T-Net) in the Task ...
Fang Liu 0034 +2 more
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PolSAR image classification using discriminative clustering
2017 International Workshop on Remote Sensing with Intelligent Processing (RSIP), 2017This paper presents a novel unsupervised image classification method for polarimetric synthetic aperture radar (PolSAR) data. The proposed method is based on a discriminative clustering framework that explicitly relies on a discriminative supervised classification technique to perform unsupervised clustering. To implement this idea, we design an energy
Haixia Bi, Jian Sun, Zongben Xu
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A Enhanced DeepLabv3+ for PolSAR image classification
2023 4th International Conference on Computer Engineering and Application (ICCEA), 2023Fang Zhang +5 more
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