Observatorio de I+D+i UPM

Memorias de investigación
Research Publications in journals:
Improving Wishart Classification of Polarimetric SAR Data Using the Hopfield Neural Network Optimization Approach
Year:2012
Research Areas
  • Physics chemical and mathematical,
  • Remote sensing
Information
Abstract
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.
International
Si
JCR
Si
Title
Remote Sensing
ISBN
2072-4292
Impact factor JCR
Impact info
Volume
4
10.3390/rs4113571
Journal number
11
From page
3571
To page
3595
Month
NOVIEMBRE
Ranking
Participants
  • Autor: Gonzalo Pajares Martinsanz (UCM)
  • Participante: Carlos López-Martínez
  • Autor: Francisco Javier Sánchez-Lladó
  • Autor: Iñigo Molina Sanchez (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: SEMEPRO: Seguridad y Mejora de Procesos
  • Departamento: Ingeniería Topográfica y Cartografía
S2i 2020 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)