Abstract
This paper proposes a novel image magnification method based on bilinear interpolation, wavelet, and partial differential equation (PDE) techniques. The image which is interpolated linearly is decomposed by wavelet into a low frequency component image and three high frequency component images, and then the three high frequency component images and the original image regarded as low-frequency component will be used for image magnification by invert wavelet transform. Finally, a PDE involving gray fidelity constraint item called improvement-self-snake mode is presented in post-processing of the magnified image. The experimental results show that the proposed linear interpolation-wavelet-PDE approach is indeed efficient and effective in image magnification. In addition, we also compare the signal-to-noise ratio (SNR) of the linear interpolation-wavelet-PDE magnification method with methods of linear interpolation, linear interpolation-wavelet, and wavelet-PDE. The simulating results show that the linear interpolation-wavelet-PDE method indeed outperforms the three kinds of image magnification approaches mentioned above.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Chen, X.F., Pan, B.C., Zheng, S.L.: Image Smooth Magnification Sengmentation Based on Curve Expression. In: Proceedings of the Seventh International Conference on Machine Learning and Cybernetics, Kunming, July 12-15, pp. 2899–2904 (2008)
Kian, K.T., Haidi, I., Siti, K.B.: Investigation on Several Basic Interpolation Methods for the Use in Remote Sensing Application. In: Proceedings of IEEE Conference on Innovative Technologies in Intelligent System and Industry Applications, pp. 60–65 (2008)
Blu, T., Thévenaz, P., Unser, M.: Linear Interpolation Revitalized. IEEE Transactions on Image Processing 13, 710–719 (2004)
Zhu, N.: Image Zooming Based on Linear Anisotropic Partial Differential Equations. Journal of Suzhou University of China 25(2), 1–7 (2010)
Mallat, S.: Multifrequency Channel Decomposition of Images and Wavelet Models. IEEE Trans. on ICASSP 37(12), 2091–2110 (1989)
Tu, G.F., Zhang, C., Wu, J.K., Liu, X.Z.: Remote Sensing Image Processing Using Wavelet Fractal Interpolation. In: International Conference on Communications, Circuits and Systems, vol. 2 (2005)
Tsai, A., Yezzi, A., Willsky, A.S.: A PDE Approach to Image Smoothing and Magnification Using the Mumford-Shah Functional. Digital Object Identifier 1, 473–477 (2000)
Xu, C., Tang, W.: A Wavelet and PDE Method for Optical Image Interpolation. In: Proceedings of 2nd International Conference on Information Science and Engineering, ICISE 2010, pp. 3498–3501 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhou, C., Lu, C., Tian, Y., Zhou, C. (2012). Image Magnification Method Based on Linear Interpolation and Wavelet and PDE. In: Huang, DS., Gan, Y., Gupta, P., Gromiha, M.M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2011. Lecture Notes in Computer Science(), vol 6839. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25944-9_90
Download citation
DOI: https://doi.org/10.1007/978-3-642-25944-9_90
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25943-2
Online ISBN: 978-3-642-25944-9
eBook Packages: Computer ScienceComputer Science (R0)