Local Geometry Driven Image Magnification and Applications to Super-Resolution
Though there have been proposed many magnification works in literatures, magnification in this paper is approached as reconstructing the geometric structures of the original high-resolution image. The structure tensor is able to estimate the orientation of both the edges and flow-like textures, which hence is much appropriate to magnification. Firstly, an edge-enhancing PDE and a corner-growing PDE are respectively proposed based on the structure tensor. Then, the two PDE’s are combined into a novel one, which not only enables to enhance the edges and flow-like textures, but also to preserve the corner structures. Finally, the novel PDE is applied to image magnification. The method is simple, fast and robust to both the noise and the blocking-artifact. Another novelty in the paper is the application of the novel PDE to super-resolution reconstruction, plus additional term for image fidelity. Experiment results demonstrate the effectiveness of our approach.
KeywordsStructure Tensor Image Magnification Bicubic Interpolation Local Coherence IEEE Signal Processing Magazine
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- 1.Tan, Y.P., Yap, K.H., Wang, L.P. (eds.): Intelligent Multimedia Processing with Soft Computing. Springer, Heidelberg (2004)Google Scholar
- 2.Vernazza, G. (ed.): The IEEE International Conference on Image Processing. Genoa, Italy (2005)Google Scholar
- 3.Huang, D.E. (ed.): The International Conference on Intelligent Computing. Springer, Heidelberg (2005)Google Scholar
- 4.Campilho, A., Kamel, M.: Image Analysis and Recognition. Springer, Heidelberg (2006)Google Scholar
- 9.Guichard, F., Malgouyres, F.: Total Variation based Interpolation. EUSIPSO III, 1741–1744 (1998)Google Scholar
- 11.Belahmidi, A., Guichard, F.: A Partial Differential Equation Approach to Image Zoom. In: Proceedings of International Conference on Image Processing (2004)Google Scholar
- 12.Morse, B.S., Schwartzwald, D.: Isophote-based Interpolation. In: 5th IEEE International Conference on Image Processing (1998)Google Scholar
- 18.Borman, S., Stevenson, R.L.: Super-resolution for Image Sequences—A Review. In: Proc. IEEE Int. Symp. Circuits and Systems, pp. 374–378 (1998)Google Scholar
- 21.Nguen, M.K., Bose, N.K.: Mathematical Analysis of Superresolution Methodology. IEEE Signal Processing Magazine, 62–74 (2003)Google Scholar
- 22.Capel, D., Zisserman, A.: Super-resolution Enhancement of Text Image Sequences. In: Proceedings of International Conference on Pattern Recognition, pp. 600–605 (2000)Google Scholar
- 23.Zomet, A., Peleg, S.: Efficient Super-resolution and Applications to Mosaics. In: Proc. Int. Conf. Pattern Recognition, pp. 579–583 (2003)Google Scholar
- 24.Banham, M.R., Katsaggelos, A.K.: Digital Image Restoration. IEEE Trans. Signal Processing, 24–41 (1997)Google Scholar