Image Super resolution Using Mid level Representations
An end to end six layers convolutional neural network(CNNs) structure is proposed to realize single image super resolution reconstruction. According to the study of image Mid Level Representations(MLR) the network layers are divided into two parts. The first part is used to obtain shallow informations by transferring features, and the second part is used to realize the feature enhancement. The input of the network is low resolution (LR) image, and the output is the superresolution (SR) image. Promising experimental results are obtained with higher precision.