Orthogonally Regularized Deep Networks for Image Super-Resolution
Orthogonally Regularized Deep Networks for Image Super-Resolution
Deep learning methods, in particular trained Convolutional Neural Networks (CNNs) have recently been shown to produce compelling state-of-the-art results for single image Super-Resolution (SR). Invariably, a CNN is learned to map the low resolution (LR) image to its corresponding high resolution (HR) version in the spatial domain. Aiming for faster …