Remote Sensing | |
Synthetic Aperture Radar Image Clustering with Curvelet Subband Gauss Distribution Parameters | |
Erkan Uslu1  | |
关键词: clustering; curvelet transform; synthetic aperture radar; self-organizing maps; | |
DOI : 10.3390/rs6065497 | |
来源: mdpi | |
【 摘 要 】
Curvelet transform is a multidirectional multiscale transform that enables sparse representations for signals. Curvelet-based feature extraction for Synthetic Aperture Radar (SAR) naturally enables utilizing spatial locality; the use of curvelet-based feature extraction is a novel method for SAR clustering. The implemented method is based on curvelet subband Gaussian distribution parameter estimation and cascading these estimated values. The implemented method is compared against original data, polarimetric decomposition features and speckle noise reduced data with use of
【 授权许可】
CC BY
© 2014 by the authors; licensee MDPI, Basel, Switzerland
【 预 览 】
Files | Size | Format | View |
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RO202003190024984ZK.pdf | 1294KB | download |