Sea Ice Change Detection in SAR Images Based on Convolutional-Wavelet Neural Networks

Sea ice change detection from synthetic aperture radar (SAR) images can be regarded as a classification procedure, in which pixels are classified into changed and unchanged classes. However, existing methods usually suffer from the intrinsic speckle noise of multitemporal SAR images. To solve the pr...

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Veröffentlicht in:	IEEE geoscience and remote sensing letters Jg. 16; H. 8; S. 1240 - 1244
Hauptverfasser:	Gao, Feng, Wang, Xiao, Gao, Yunhao, Dong, Junyu, Wang, Shengke
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.08.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks Change detection Change detection algorithms Classification convolutional-wavelet neural network (CWNN) Detection Image classification Image detection Neural networks Pixels Radar detection Radar imaging SAR (radar) Sea ice Speckle Synthetic aperture radar synthetic aperture radar (SAR) images Training Wavelet transforms
ISSN:	1545-598X, 1558-0571
Online-Zugang:	Volltext
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