Research on Single Image Super-Resolution Reconstruction Method Based on Dual-Stream U-Shape
Deep neural networks have attracted widespread attention in image super-resolution.However,many super-resolution networks ignore the contribution of multiple different feature information to image recon-struction.To address the above problems,a double-stream U-shaped super-resolution network is designed,which utilizes the different scales of feature maps generated in the U-shaped structure to reconstruct image fea-tures,and also uses a novel projection structure to enhance the representation of disparate features.In addition,a lightweight network is designed in order to be embedded into realistic small devices.Experiments show that the designed networks achieve good metric values and high quality visualization on popular datasets.
deep neural networksuper-resolutionfeature extraction flowlightweight network
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