This paper combines the popular multi-scale convolution and channel attention mechanism,and proposes a novel convolutional neural network(CNN)structure,namely the multi-scale CNN un-der attention mechanism.A large number of residual structures are added to the proposed network structure,which deepens the depth of the network.The utilization of multi-scale convolution enables the network to extract richer information from pictures.The introduction of the attention mechanism enables the network to have greater weight in processing high-frequency information.Experimental results show that the multi-scale CNN under attention mechanism has achieved good performance in image super-resolution(SR)reconstruction,and the effect of image detail restoration is satisfactory.
维普
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