Remote Sensing Image Registration Using Convolutional Neural Network Features

Successful remote sensing image registration is an important step for many remote sensing applications. The scale-invariant feature transform (SIFT) is a well-known method for remote sensing image registration, with many variants of SIFT proposed. However, it only uses local low-level information, a...

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Veröffentlicht in:	IEEE geoscience and remote sensing letters 2018-02, Vol.15 (2), p.232-236
Hauptverfasser:	Ye, Famao, Su, Yanfei, Xiao, Hui, Zhao, Xuqing, Min, Weidong
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Convolutional neural network (CNN) Detection Feature extraction Image classification Image registration Levels Methods Neural networks Registers Registration Remote sensing remote sensing image registration Robustness scale-invariant feature transform (SIFT) State of the art Transforms
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