Identifying Corresponding Patches in SAR and Optical Images with a Pseudo-Siamese CNN

25 Jan 2018Lloyd H. HughesMichael SchmittLichao MouYuanyuan WangXiao Xiang Zhu

In this letter, we propose a pseudo-siamese convolutional neural network (CNN) architecture that enables to solve the task of identifying corresponding patches in very-high-resolution (VHR) optical and synthetic aperture radar (SAR) remote sensing imagery. Using eight convolutional layers each in two parallel network streams, a fully connected layer for the fusion of the features learned in each stream, and a loss function based on binary cross-entropy, we achieve a one-hot indication if two patches correspond or not... (read more)

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