Region-based classification of PolSAR data using radial basis kernel functions with stochastic distances

Region-based classification of PolSAR data can be effectively performed by seeking for the assignment that minimizes a distance between prototypes and segments. Silva et al. ["Classification of segments in PolSAR imagery by minimum stochastic distances between wishart distributions." IEEE...

Full description

Saved in:

Bibliographic Details
Published in:	International journal of digital earth Vol. 12; no. 6; pp. 699 - 719
Main Authors:	Negri, Rogério G., Frery, Alejandro C., Silva, Wagner B., Mendes, Tatiana S. G., Dutra, Luciano V.
Format:	Journal Article
Language:	English
Published:	Abingdon Taylor & Francis 03-06-2019 Taylor & Francis Ltd Taylor & Francis Group
Subjects:	Case studies Classification Computer applications Computer simulation Distance Earth Image classification Imagery Kernel functions Mathematical models minimum distance classifier PolSAR Prototypes Remote sensing Reproducibility Robustness (mathematics) Segments stochastic distance Stochasticity Support vector machines SVM Training
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!