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Gradient Profile Prior and Its Applications in Image Super-Resolution and Enhancement

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4 Author(s)
Jian Sun ; School of Science, Xi'an Jiaotong University, Xi'an, China ; Jian Sun ; Zongben Xu ; Heung-Yeung Shum

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.

Published in:

IEEE Transactions on Image Processing  (Volume:20 ,  Issue: 6 )