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

Remote Sensing

Volumn 4, Issue 11, 2012, Pages 3571-3595

  Pajares, Gonzalo ^a   López Martínez, Carlos ^b   Sánchez Lladó, F Javier ^b   Molina, Íñigo ^c  

^a UNIVERSIDAD COMPLUTENSE DE MADRID   (Spain)

^b UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

^c UNIVERSIDAD POLITÉCNICA DE MADRID   (Spain)

Author keywords

Hopfield neural networks; Image classification; Optimization; Polarimetric synthetic aperture radar (PolSAR); Wishart classifier

Indexed keywords

CLASSIFICATION RESULTS; COMPLEX WISHART DISTRIBUTIONS; CONSISTENCY COEFFICIENT; HOPFIELD NEURAL NETWORK OPTIMIZATIONS; IMAGE DATA; MAXIMUM LIKELIHOOD CLASSIFIERS; OPTIMIZATION APPROACH; OPTIMIZATION PROCESS; POLARIMETRIC SAR DATA; POLARIMETRIC SYNTHETIC APERTURE RADARS;

CLUSTER COMPUTING; IMAGE CLASSIFICATION; OPTIMIZATION; PIXELS; POLARIMETERS; PROGRAM PROCESSORS; SYNTHETIC APERTURE RADAR;

HOPFIELD NEURAL NETWORKS;

EID: 84870840688     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs4113571     Document Type: Article

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