Multiscale Unsupervised Segmentation of SAR Imagery Using the Genetic Algorithm

A valid unsupervised and multiscale segmentation of synthetic aperture radar (SAR) imagery is proposed by a combination GA-EM of the Expectation Maximization (EM) algorith with the genetic algorithm (GA). The mixture multiscale autoregressive (MMAR) model is introduced to characterize and exploit th...

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Detalles Bibliográficos
Autores principales: Wen, Xian-Bin, Zhang, Hua, Jiang, Ze-Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2008
Materias:
Full Research Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3663018/
https://www.ncbi.nlm.nih.gov/pubmed/27879787

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3663018/
https://www.ncbi.nlm.nih.gov/pubmed/27879787

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