Results 181 to 190 of about 2,015 (220)
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Weighted Wishart distance learning for PolSAR image classification
International Journal of Remote Sensing, 2017ABSTRACTAn approach of weighted Wishart distance learning, shorted for W2-based distance learning, is proposed for polarimetric synthetic aperture radar (PolSAR) image classification. It aims to adjust the Wishart distance by enhancing discrimination as well as exploiting spatial information. The proposed distance learning keeps samples within the same
Chen Sun +3 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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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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Riemannian sparse coding for classification of PolSAR images
2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016Hermitian positive definite (HPD) covariance matrices form one of the most widely-used data representations in PolSAR applications. However, most of these applications either use statistical distribution models on the PolSAR covariance matrices or polarimetric target decomposition. In this paper, we study HPD matrices for PolSAR image classification in
Wen Yang +3 more
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Classification-oriented hyperspectral and PolSAR images synergic processing
2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS, 2013Classification is one of the most important applications in the field of remote sensing. How to improve the accuracy of classification is the critical topic that has long obsessed the researchers. In this paper, a fusion method based on a synergic use of hyperspectral data and Polarimetric SAR (PolSAR) data is presented.
Tong Li +3 more
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PolSAR image speckle reduction based on pixels classification
2012 IEEE 11th International Conference on Signal Processing, 2012An effective algorithm for PolSAR image speckle reduction is developed in this paper. First, pixels in the image are classified through three steps: i) HH/α plane is used for image initial classification based on the polarization difference; ii) anisotropy A and total backscattering power after PWF are combined for further classification; iii ...
Ping Han, Xiaohong Yu, Fei Dong
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PolSAR image fast classification based on random similarity
2017 Progress In Electromagnetics Research Symposium - Spring (PIERS), 2017Random similarity is used to construct an entropy/alpha-like classification of PolSAR image in terms of two parameters, i.e., the similarity-based angle α s and entropy H s . α s and H s are analogous to the Cloude-Pottier angle α and entropy H to characterize scattering mechanism and randomness, respectively.
Dong Li, Yunhua Zhang, Feiya Zhu
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Fuzzy Support Vector Machine for PolSAR Image Classification
Advanced Materials Research, 2013Fully Polarimetric Synthetic Aperture Radar (PolSAR) image classification, with the complexity for its data’s scattering mechanism and statistical property, has expected to be performed by an automatic categorization. This paper presents a supervised method called Fuzzy support vector machine (FSVM), which is a variant of the SVM algorithm to classify ...
Hong Xia Ke, Guo Dong Liu, Guo Bing Pan
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Unsupervised PolSAR image classification based on sparse representation
International Journal of Remote Sensing, 2019A novel unsupervised image classification algorithm which based on the sparse representation theory for polarimetric synthetic aperture radar (PolSAR) image is introduced in this paper.
Yaqi Ji +3 more
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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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