Edge Attention Network for Image Deblurring and Super-Resolution

While deep learning-based single image super-resolution has progressed significantly, super-resolution of images containing blurring artifacts is still challenging. This paper proposes a unified model that can simultaneously perform deblurring and super-resolution for a given image, which is called Edge Attention Network (EAN). Our model employs an attention mechanism using the edge information in order to enhance the sharpness of the super-resolved output image. Experimental results demonstrate that our method outperforms existing super-resolution methods and separate application of deblurring and super-resolution.

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