Results 91 to 100 of about 12,268,087 (190)

PolSAR Image Classification with Active Complex-Valued Convolutional-Wavelet Neural Network and Markov Random Fields

PolSAR image classification has attracted extensive significant research in recent decades. Aiming at improving PolSAR classification performance with speckle noise, this paper proposes an active complex-valued convolutional-wavelet neural network by ...
Lu Liu, Yongxiang Li
core   +1 more source

A novel semicoupled projective dictionary pair learning method for PolSAR image classification

, 2019
Polarimetric synthetic aperture radar (PolSAR) image classification plays an important role in remote sensing image processing. In recent years, stacked auto-encoder (SAE) has obtained a series of excellent results in PolSAR image classification.
Chen, Yanqiao, Jiao, Licheng, Li, Yangyang, Ren, Bo, Marturi, Naresh, Zhang, Dan, Li, Lingling   +6 more
core   +1 more source

Ice Volume Characterization using Long-Wavelength Airborne PolSAR Data [PDF]

, 2012
The interest in studying land ice for glaciological and climate change research has increased in recent years. The need of information on a global scale makes synthetic aperture radar (SAR) suitable for these studies.
Konstantinos P. Papathanassiou, Jagdhuber, Thomas, Papathanassiou, Konstantinos P., Hajnsek, Irena, Parrella, Giuseppe, Al-Kahachi, Noora, Papathanassiou, Kostantinos, Thomas Jagdhuber, Noora Al-Kahachi, Irena Hajnsek, Giuseppe Parrella   +10 more
core   +1 more source

Covariance Symmetries Classification in Multitemporal/Multipass PolSAR Images

IEEE Transactions on Geoscience and Remote Sensing
A polarimetric synthetic aperture radar (PolSAR) system, which uses multiple images acquired with different polarizations in both transmission and reception, has the potential to improve the description and interpretation of the observed scene. This is typically achieved by exploiting the polarimetric covariance or coherence matrix associated with each
Dehbia Hanis, Luca Pallotta, Augusto Aubry, Aichouche Belhadj Aissa, Antonio De Maio   +4 more
openaire   +3 more sources

Auto Encoder Feature Learning with Utilization of Local Spatial Information and Data Distribution for Classification of PolSAR Image

, 2019
The distribution of data plays a key role in the designing of a machine learning model. Therefore, this paper proposes a novel auto encoder network based on the distribution of polarimetric synthetic aperture radar (PolSAR) data matrix.
Shuang Wang, Licheng Jiao, Jianlong Wang, Biao Hou   +3 more
core   +1 more source

Multiview Manifold Evidential Fusion for PolSAR Image Classification

CoRR
The paper has 14 pages and 7 ...
Junfei Shi, Haojia Zhang, Haiyan Jin, Junhuai Li, Xiaogang Song, Yuanfan Guo, Haonan Su, Weisi Lin   +7 more
openaire   +2 more sources

Sparse Subspace Clustering-Based Feature Extraction for PolSAR Imagery Classification

, 2018
Features play an important role in the learning technologies and pattern recognition methods for polarimetric synthetic aperture (PolSAR) image interpretation.
Bo Ren, Jin Zhao, Licheng Jiao, Biao Hou
core   +1 more source

A Dense Bootstrap Contrastive Learning Method With 3-D Dynamic Convolution for Few-Shot PolSAR Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
High-quality labeled samples of polarimetric synthetic aperture radar (PolSAR) images are relatively scarce. Therefore, achieving optimal classification performance with limited labeled samples has become a significant challenge in PolSAR image ...
Nana Jiang, Wenbo Zhao, Jiao Guo, Xiuya Dong, Jubo Zhu   +4 more
doaj   +1 more source

Superpixel-Based Classification Using K Distribution and Spatial Context for Polarimetric SAR Images

Remote Sensing, 2016
Classification techniques play an important role in the analysis of polarimetric synthetic aperture radar (PolSAR) images. PolSAR image classification is widely used in the fields of information extraction and scene interpretation or is performed as a ...
Qiao Xu, Qihao Chen, Shuai Yang, Xiuguo Liu   +3 more
doaj   +1 more source

MAPM:PolSAR Image Classification with Masked Autoencoder Based on Position Prediction and Memory Tokens

Remote Sensing
Deep learning methods have shown significant advantages in polarimetric synthetic aperture radar (PolSAR) image classification. However, their performances rely on a large number of labeled data.
Jianlong Wang, Yingying Li, Dou Quan, Beibei Hou, Zhensong Wang, Haifeng Sima, Junding Sun   +6 more
doaj   +1 more source