Image Super-Resolution Using TV Priori Guided Convolutional Network
This addresses image quality enhancement for applications like photography or medical imaging, but appears incremental as it builds on existing deep learning and TV prior methods.
The paper tackles single image super-resolution by proposing a TV priori guided convolutional network that learns an end-to-end mapping from low- to high-resolution images, but no concrete results or numbers are provided.
We proposed a TV priori information guided deep learning method for single image super-resolution(SR). The new alogorithm up-sample method based on TV priori, new learning method and neural networks architecture are embraced in our TV guided priori Convolutional Neural Network which diretcly learns an end to end mapping between the low level to high level images.