Image Super-Resolution using Gradient Profile Prior
Computer Graphics and Modern Art
Super resolution is one of the most important tasks in computer vision and computer graphics. We will implement a super-resolution approach using a novel generic image prior – gradient profile prior, which is a parametric prior describing the shape and the sharpness of the image gradients. Using the gradient profile prior learned from a large number of natural images, we can provide a constraint on image gradients when we estimate a hi-resolution image from a low-resolution image. With this simple but very effective prior, we are able to produce state-of-the-art results. The reconstructed high-resolution image is sharp while has rare ringing or jaggy artifacts.
In this project we will develop
algorithm and create an application.