Fully Statistical, Wavelet-based conditional random field (FSWCRF) for SAR image segmentation

•A new statistical conditional random field is proposed for SAR image segmentation.•The generalized Gaussian distribution of wavelet coefficients is applied in the CRF.•The unary potential is constructed based on the generalized Gaussian distribution.•The Kullback–Leibler distance improves the pairw...

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Vydané v:	Expert systems with applications Ročník 168; s. 114370
Hlavní autori:	Golpardaz, Maryam, Helfroush, Mohammad Sadegh, Danyali, Habibollah, Ghaffari, Reyhane
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Elsevier Ltd 15.04.2021 Elsevier BV
Predmet:	Algorithms Conditional Random Field (CRF) Conditional random fields Distribution functions Feature extraction Generalized Gaussian Distributions (GGD) Image segmentation Kullback–Leibler Distance (KLD) Normal distribution Parameters Radar imaging Regression models Similarity Similarity measures Statistical analysis Synthetic aperture radar Synthetic Aperture Radar (SAR) image segmentation Two dimensional models Wavelet transforms Conditional Random Field (CRF) Generalized Gaussian Distributions (GGD) Synthetic Aperture Radar (SAR) image segmentation Kullback–Leibler Distance (KLD)
ISSN:	0957-4174, 1873-6793
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