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Improving wishart classification of polarimetric SAR data using the hopfield neural network optimization approach

Autor
Pajares, G.; Lopez, C.; Sánchez, F.; Molina, I.
Tipus d'activitat
Article en revista
Revista
Remote sensing
Data de publicació
2012-11-19
Volum
4
Número
11
Pàgina inicial
3571
Pàgina final
3595
DOI
https://doi.org/10.3390/rs4113571 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/87165 Obrir en finestra nova
URL
http://www.mdpi.com/2072-4292/4/11/3571 Obrir en finestra nova
Resum
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. We consider the initial classification provided by the maximum-likelihood classifier based on the complex Wishart distribution, which is then supplied to the HNN optimization approach. The goal is to improve the classification results obtained by the Wishart approach. The classification imp...
Citació
Pajares, G., Lopez, C., Sánchez, F., Molina, I. Improving wishart classification of polarimetric SAR data using the hopfield neural network optimization approach. "Remote sensing", 19 Novembre 2012, vol. 4, núm. 11, p. 3571-3595.
Paraules clau
Hopfield Neural Networks, Image Classification, Optimization, Polarimetric Synthetic Aperture Radar (polsar), Wishart Classifier
Grup de recerca
RSLAB - Grup de Recerca en Teledetecció

Participants

  • Pajares Martinsanz, Gonzalo  (autor)
  • López Martínez, Carlos  (autor)
  • Sánchez Lladó, Francisco Javier  (autor)
  • Molina, Iñigo  (autor)