Results 11 to 20 of about 3,144 (202)

PolSAR-SFCGN: An End-to-End PolSAR Superpixel Fully Convolutional Generation Network

Remote Sensing
Polarimetric Synthetic Aperture Radar (PolSAR) image classification is one of the most important applications in remote sensing. The impressive superpixel generation approaches can improve the efficiency of the subsequent classification task and restrain
Mengxuan Zhang, Jingyuan Shi, Long Liu, Wenbo Zhang, Jie Feng, Jin Zhu, Boce Chu   +6 more
doaj   +3 more sources

PolSAR Models with Multimodal Intensities

Remote Sensing, 2022
Polarimetric synthetic aperture radar (PolSAR) systems are an important remote sensing tool. Such systems can provide high spacial resolution images, but they are contaminated by an interference pattern called multidimensional speckle. This fact requires
Jodavid A. Ferreira, Abraão D. C. Nascimento, Alejandro C. Frery   +2 more
core   +6 more sources

The Improved Three-Step Semi-Empirical Radiometric Terrain Correction Approach for Supervised Classification of PolSAR Data

Remote Sensing, 2022
The radiometric terrain correction (RTC) is an essential processing step for supervised classification applications of polarimetric synthetic aperture radar (PolSAR) over mountainous areas.
Lei Zhao, Erxue Chen, Zengyuan Li, Yaxiong Fan, Kunpeng Xu   +4 more
doaj   +2 more sources

Evaluation of Polsar Similarity Measures with Spectral Clustering

2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017
Polarimetric Synthetic Aperture Radar (PolSAR) is a valuable remote sensing data source. It is usually challenging to interpret PolSAR data, especially in urban areas, and hense, spatial clustering comes as a powerful tool for the application of PolSAR ...
Wang, Yuanyuan, Ghamisi, Pedram, Yuanyuan Wang, Pedram Ghamisi, Jingliang Hu, Hu, Jingliang, Zhu, Xiaoxiang, Xiao Xiang. Zhu   +7 more
core   +3 more sources

The Highly Compressed PolSAR Model

IEEE Transactions on Radar Systems
Additional scene information can be captured using fully polarimetric synthetic aperture radar (PolSAR) at the cost of significant increases in storage and data processing requirements.
Becker, John, Jackson, Julie Ann
core   +2 more sources

Prototype Theory Based Feature Representation for PolSAR Images

Leida xuebao, 2016
This study presents a new feature representation approach for Polarimetric Synthetic Aperture Radar (PolSAR) image based on prototype theory. First, multiple prototype sets are generated using prototype theory.
Huang Xiaojing, Yang Xiangli, Huang Pingping, Yang Wen   +3 more
doaj   +2 more sources

Heterogeneous Network-Based Contrastive Learning Method for PolSAR Land Cover Classification [PDF]

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Polarimetric synthetic aperture radar (PolSAR) image interpretation is widely used in various fields. Recently, deep learning has made significant progress in PolSAR image classification. Supervised learning (SL) requires a large amount of labeled PolSAR
Jianfeng Cai, Yue Ma, Zhixi Feng, Shuyuan Yang, Licheng Jiao   +4 more
doaj   +2 more sources

Phase Characterization of PolSAR Images

, 2007
PolSAR images can be characterized by their phase ...
Datcu, Mihai, Soccorsi, Matteo
core   +2 more sources

Adversarial Reconstruction-Classification Networks for PolSAR Image Classification

Remote Sensing, 2019
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, Yangyang Li, Licheng Jiao, Cheng Peng, Xiangrong Zhang, Ronghua Shang   +5 more
doaj   +2 more sources

MCDiff: A Multilevel Conditional Diffusion Model for PolSAR Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
With the swift advancement of deep learning, significant strides have been made in polarimetric synthetic aperture radar (PolSAR) image classification, particularly with the advent of diffusion models that allow for explicit class probability modeling ...
Qingyi Zhang, Xiaoxiao Fang, Tao Liu, Ronghua Wu, Liguo Liu, Chu He   +5 more
doaj   +2 more sources