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Gradient Profile Prior and Its Applications in Image Super-Resolution and Enhancement.
- Source :
- IEEE Transactions on Image Processing; Jun2011, Vol. 20 Issue 6, p1529-1542, 14p
- Publication Year :
- 2011
-
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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10577149
- Volume :
- 20
- Issue :
- 6
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Image Processing
- Publication Type :
- Academic Journal
- Accession number :
- 60832086
- Full Text :
- https://doi.org/10.1109/TIP.2010.2095871