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Single image super-resolution using global enhanced upscale network

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Current works on super-resolution have obtained satisfactory results since the advance of the convolution neural network. Nevertheless, most previous works use one network for one integer scale factor so ignore… Click to show full abstract

Current works on super-resolution have obtained satisfactory results since the advance of the convolution neural network. Nevertheless, most previous works use one network for one integer scale factor so ignore the super-resolution of the arbitrary scale factor. In this work, we propose a novel approach called Global Enhanced Upscale Network (GEUN) to tackle super-resolution with a single model adapting the arbitrary scale factor. In our GEUN, we propose the Global Enhanced Upscale module to replace the conventional upscale module. Our GEUN can upscale low-resolution images with an arbitrary scale factor through only one model. Extensive experimental results demonstrate the superiority of our GEUN.

Keywords: resolution; network; enhanced upscale; global enhanced; super resolution; scale factor

Journal Title: Applied Intelligence
Year Published: 2021

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