SITSAR: Information Theory, Geometry and Statistics for SAR Data

Statistical models, information-theoretic measures and image analysis tools for Synthetic Aperture Radar (SAR) and polarimetric SAR (PolSAR) data, gathering the methods developed in the master's dissertation (divergence-based classifiers) and the PhD thesis (Shannon entropies, entropy-based segmentation and change detection, and compound Wishart models) of Jodavid A. Ferreira, supervised by Abraão D. C. Nascimento.

Main tools

Distributions

dg0i, dgammasar, dggamma, dwishart_sar, dg0p, compound_wishart.

R6 models

GammaSAR, G0I, GGammaSAR, WishartSAR, G0Polarimetric, CompoundWishart (estimation, entropy and asymptotic variance).

Images

SARImage, sar_features(), entropy_map(), plot_map().

Segmentation and change detection

EntropySegmenter, segment_sar(), entropy_test(), change_map().

Classification

divergences, DivergenceClassifier and the 'parsnip' model divergence_classifier().

Accuracy

kappa_statistics(), change_detection_metrics().

See also

Useful links:

• https://github.com/jodavid/SITSAR

• https://jodavid.github.io/SITSAR/

• Report bugs at https://github.com/jodavid/SITSAR/issues

Author

Maintainer: Jodavid Ferreira jodavid@protonmail.com (ORCID)

Authors:

• Jodavid Ferreira jodavid@protonmail.com (ORCID)

• Abraao Nascimento abraao@de.ufpe.br (ORCID)