Parameter estimation in SAR imagery using stochastic distances and asymmetric kernels

In this paper, we analyze several strategies for the estimation of the roughness parameter of the GI 0 distribution. It has been shown that this distribution is able to characterize a large number of targets in monopolarized synthetic aperture radar (SAR) imagery, deserving the denomination of '...

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Detalles Bibliográficos
Autores principales: Gambini, J., Cassetti, J., Lucini, M.M., Frery, A.C.
Formato: JOUR
Materias:
Feature extraction
image texture analysis
speckle
statistics
Synthetic aperture radar (SAR)
Image texture
Radar
Radar imaging
Speckle
Statistics
Stochastic systems
Synthetic aperture radar
Textures
Image texture analysis
Inverse Gaussian density
Numerical problems
Roughness parameters
Synthetic Aperture Radar Imagery
Texture parameters
Theoretical density
Three parameters
Parameter estimation
image analysis
imagery
roughness
stochasticity
synthetic aperture radar
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_19391404_v8_n1_p365_Gambini
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

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