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Memorias de investigación
Artículos en revistas:
Improving Wishart Classification of Polarimetric SAR Data Using the Hopfield Neural Network Optimization Approach
Año:2012
Áreas de investigación
  • Física química y matemáticas,
  • Teledetección
Datos
Descripción
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 improvement is verified by computing a cluster separability coefficient and a measure of homogeneity within the clusters. During the HNN optimization process, for each iteration and for each pixel, two consistency coefficients are computed, taking into account two types of relations between the pixel under consideration and its corresponding neighbors. Based on these coefficients and on the information coming from the pixel itself, the pixel under study is re-classified. Different experiments are carried out to verify that the proposed approach outperforms other strategies, achieving the best results in terms of separability and a trade-off with the homogeneity preserving relevant structures in the image. The performance is also measured in terms of computational central processing unit (CPU) times.
Internacional
Si
JCR del ISI
Si
Título de la revista
Remote Sensing
ISSN
2072-4292
Factor de impacto JCR
Información de impacto
Volumen
4
DOI
10.3390/rs4113571
Número de revista
11
Desde la página
3571
Hasta la página
3595
Mes
NOVIEMBRE
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Participantes
  • Autor: Gonzalo Pajares Martinsanz (UCM)
  • Participante: Carlos López-Martínez
  • Autor: Francisco Javier Sánchez-Lladó
  • Autor: Iñigo Molina Sanchez (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: SEMEPRO: Seguridad y Mejora de Procesos
  • Departamento: Ingeniería Topográfica y Cartografía
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