Results 91 to 100 of about 2,015 (220)

Statistical assessment of eigenvector-based target decomposition theorems in radar polarimetry [PDF]

, 2005
© 2005 IEEE.Carlos López-Martínez, Eric Pottier and Shane R ...
Cloude, Shane Robert, Lopez-Martinez, Carlos, Pottier, Eric   +2 more
core   +2 more sources

Pearl Millet Crop Biophysical Parameter Retrieval From Space Borne Polarimetric SAR Data Using Machine Learning

Earth and Space Science, Volume 11, Issue 1, January 2024.
Abstract The potential of single date fully Polarimetric RADARSAT‐2 data in retrieving crop biophysical parameters using Machine Learning techniques was investigated. Various polarimetric parameters along with coherent and incoherent decomposition techniques were assessed for its sensitivity toward crop parameters like Wet and Dry Biomass, Crop Height,
Dharanya Thulasiraman, Dipanwita Haldar, Shashi Kumar, Arun Balaji Ramathilagam, N. R. Patel   +4 more
wiley   +1 more source

Semi-supervised PolSAR Image Classification Based on the Neighborhood Minimum Spanning Tree

Leida xuebao, 2019
In this paper, a novel semi-supervised classification method based on the Neighborhood Minimum Spanning Tree (NMST) is proposed to solve the Polarimetric Synthetic Aperture Radar (PolSAR) terrain classification when labeled samples are few. Combining the
HUA Wenqiang, WANG Shuang, GUO Yanhe, XIE Wen   +3 more
doaj   +1 more source

Fuzzy Superpixels Based Semi-Supervised Similarity-Constrained CNN for PolSAR Image Classification

Remote Sensing, 2020
Recently, deep learning has been highly successful in image classification. Labeling the PolSAR data, however, is time-consuming and laborious and in response semi-supervised deep learning has been increasingly investigated in PolSAR image classification.
Yuwei Guo, Zhuangzhuang Sun, Rong Qu, Licheng Jiao, Fang Liu, Xiangrong Zhang   +5 more
doaj   +1 more source

Improving Wishart Classification of Polarimetric SAR Data Using the Hopfield Neural Network Optimization Approach. [PDF]

, 2012
This paper proposes the optimization relaxation approach based on the analogue Hopfield Neural Network (HNN) for cluster refinement of pre-classified Polarimetric Synthetic Aperture Radar (PolSAR) image data.
Carlos López-Martínez, Cloude, Cloude, Cloude, Cohen, Cui, Davies, Du, F. Sánchez-Lladó, Ferro-Famil, Gonzalo Pajares, Grandi, Hajek, Hara, Haykin, Hopfield, Hopfield, Joya, Kasetkasem, Kosko, Lee, Lee, Lee, Lee, Lee, Müezzinoglu, Qiao, Starink, Sánchez-Lladó, Turner, van Laarhoven, Wang, Yu, Zhao, Íñigo Molina   +34 more
core   +7 more sources

CFAR Hierarchical Clustering of Polarimetric SAR Data [PDF]

, 2013
International audienceRecently, a general approach for high-resolution polarimetric SAR (POLSAR) data classification in heterogeneous clutter was presented, based on a statistical test of equality of covariance matrices.
Chanussot, Jocelyn, Formont, Pierre, Frontera-Pons, Joana, Ovarlez, Jean-Philippe, Pascal, Frédéric, Veganzones, Miguel Angel   +5 more
core   +4 more sources

Evaluación de la degradación de la tierra usando la entropía de shannon sobre imágenes polarimétricas en desiertos costeros Patagónicos [PDF]

, 2013
En esta investigación se focalizó en la Entropía de Shannon (ES) para la caracterización de imágenes polarimétricas de apertura sintética. Este parámetro analiza la contribución de la información por pixeles individuales para toda la imagen en la ...
Blanco, Paula Daniela, del Valle, Hector Francisco, Hardtke, Leonardo Andrés, Sione, Walter Fabian   +3 more
core   +1 more source

Global Polarimetric Synthetic Aperture Radar Image Segmentation with Data Augmentation and Hybrid Architecture Model

Remote Sensing
Machine learning and deep neural networks have shown satisfactory performance in the supervised classification of Polarimetric Synthetic Aperture Radar (PolSAR) images. However, the PolSAR image classification task still faces some challenges. First, the
Zehua Wang, Zezhong Wang, Xiaolan Qiu, Zhe Zhang   +3 more
doaj   +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   +2 more sources

Robust Classification of PolSAR Images Based on Pinball loss Support Vector Machine

Leida xuebao, 2019
Given the problems that the amount of supervised information in the Polarimetric Synthetic Aperture Radar (PolSAR) image is low and the speckle noise is difficult to eliminate, in this study, a robust classification algorithm for PolSAR image based on ...
ZHANG Lamei, ZHANG Siyu, DONG Hongwei, ZHU Sha   +3 more
doaj   +1 more source