Cloud Removal of Satellite Image Using Edge-Guided Convolutional Neural Network
Cloud removal of remote sensing images is one of the important technologies to improve data quality and reduce data cost.A novel network structure to reconstruct missing in-formation in images,which is called edge-guided gated convo-lutional network(EGCN),is put forward via the applications of convolutional neural network in cloud removal task using Landsat 8 images.This network uses multi-temporal data as auxiliary data for padding cloudy images.Spatial-temporal based gated convolutional network(STGCN)is used as the main trunk and an improved non-local(NL)block called gated non-local(GNL)is introduced to replace the traditional convolution layers.Besides,an edge network(ENet)is used as a branch to guide the feature from the edge information level.The experimental results show that GNL and ENet both bene-fit cloud removal task.
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