12-04-2012, 01:11 PM
GRADIENT PROFILE PRIOR AND ITS APPLICATIONS IN IMAGE SUPER-RESOLUTION AND ENHANCEMENT
ABSTRACT
In this paper, we propose a novel generic image prior-gradient profile prior, which implies the prior knowledge of natural image gradients. In this prior, the image gradients are represented by gradient profiles, which are 1-D profiles of gradient magnitudes perpendicular to image structures.
We model the gradient profiles by a parametric gradient profile model. Using this model, the prior knowledge of the gradient profiles are learned from a large collection of natural images, which are called gradient profile prior.
Based on this prior, we propose a gradient field transformation to constrain the gradient fields of the high resolution image and the enhanced image when performing single image super-resolution and sharpness enhancement. With this simple but very effective approach, we are able to produce state-of-the-art results.
The reconstructed high resolution images or the enhanced images are sharp while have rare ringing or jaggy artifacts