Superpixel Generation for SAR Imagery Based on Fast DBSCAN Clustering With Edge Penalty

In this article, we propose an adaptive superpixel generation algorithm for synthetic aperture radar (SAR) imagery, which is implemented based on fast density-based spatial clustering of applications with noise (DBSCAN) clustering and superpixel merging with edge penalty. The superpixel generation a...

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Vydané v:	IEEE journal of selected topics in applied earth observations and remote sensing Ročník 15; s. 804 - 819
Hlavní autori:	Zhang, Liang, Lu, Shengtao, Hu, Canbin, Xiang, Deliang, Liu, Tao, Su, Yi
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Accuracy Adaptive algorithms Algorithms Clustering Clustering algorithms Data interpretation density-based spatial clustering of applications with noise (DBSCAN) edge penalty Image classification Image edge detection Image segmentation Imagery Merging Methods Pixels Radar imaging Radar polarimetry SAR (radar) Speckle superpixel generation Synthetic aperture radar synthetic aperture radar (SAR) image
ISSN:	1939-1404, 2151-1535
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