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Image resolution enhancement using dual-tree complex wavelet transform

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Çelik, Turgay and Tjahjadi, Tardi. (2010) Image resolution enhancement using dual-tree complex wavelet transform. Geoscience and Remote Sensing Letters, Vol.7 (No.3). pp. 554-557. ISSN 1545-598X

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Official URL: http://dx.doi.org/10.1109/LGRS.2010.2041324

Abstract

In this letter, a complex wavelet-domain image resolution enhancement algorithm based on the estimation of wavelet coefficients is proposed. The method uses a forward and inverse dual-tree complex wavelet transform (DT-CWT) to construct a high-resolution (HR) image from the given low-resolution (LR) image. The HR image is reconstructed from the LR image, together with a set of wavelet coefficients, using the inverse DT-CWT. The set of wavelet coefficients is estimated from the DT-CWT decomposition of the rough estimation of the HR image. Results are presented and discussed on very HR QuickBird data, through comparisons between state-of-the-art resolution enhancement methods.

Item Type:	Journal Article
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Science > Engineering
Library of Congress Subject Headings (LCSH):	Image processing -- Digital techniques, Wavelets (Mathematics)
Journal or Publication Title:	Geoscience and Remote Sensing Letters
Publisher:	Institute of Electrical and Electronics Engineers
ISSN:	1545-598X
Date:	July 2010
Volume:	Vol.7
Number:	No.3
Number of Pages:	4
Page Range:	pp. 554-557
Identification Number:	10.1109/LGRS.2010.2041324
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Funder:	University of Warwick Vice Chancellor Scholarship
References:	[1] X. Li and M. Orchard, “New edge-directed interpolation,” IEEE Trans. Image Proc., vol. 10, no. 10, pp. 1521–1527, Oct 2001. [2] L. Zhang and X. Wu, “An edge-guided image interpolation algorithm via directional filtering and data fusion,” IEEE Trans. Image Proc., vol. 15, no. 8, pp. 2226–2238, Aug 2006. [3] W. K. Carey, D. B. Chuang, and S. S. Hemami, “Regularity-preserving image interpolation,” IEEE Trans. Image Proc., vol. 8, no. 9, pp. 1293–1297, 1999. [4] S. Chang, Z. Cvetkovic, and M. Vetterli, “Locally adaptive wavelet-based image interpolation,” IEEE Transactions on Image Processing, vol. 15, no. 6, pp. 1471–1485, Jun 2006. [5] K. Kinebuchi, D. D. Muresan, and T. W. Parks, “Image interpolation using wavelet-based hidden markov trees,” in Proc. IEEE Int. Conf. Acoust. Speech and Signal Process., 2001, pp. 1957–1960. [6] A. Temizel and T. Vlachos, “Wavelet domain image resolution enhancement using cycle-spinning,” Electronics Letters, vol. 41, no. 3, pp. 119–121, Feb 2005. [7] N. Kingsbury, “Complex wavelets for shift invariant analysis and filtering of signals,” J. Appl. Comput. Harmon. Anal., vol. 10, no. 3, pp. 234–253, 2001. [8] L. Alparone, S. Baronti, A. Garzelli, and F. Nencini, “Landsat etm+ and sar image fusion based on generalized intensity modulation,” IEEE Transactions on Geoscience and Remote Sensing, vol. 42, no. 12, pp. 2832–2839, Dec 2004. [9] C.-I. Chang, “Spectral information divergence for hyperspectral image analysis,” in Proceedings of IEEE International Geoscience and Remote Sensing Symposium, vol. 1, 1999, pp. 509–511. [10] L. Alparone, S. Baronti, A. Garzelli, and F. Nencini, “A global quality measurement of pan-sharpened multispectral imagery,” IEEE Geoscience and Remote Sensing Letters, vol. 1, no. 4, pp. 313–317, Oct 2004. [11] L. Wald, “Quality of high resolution synthesized images: Is there a simple criterion?” in Proceedings of International Conference on Fusion of Earth Data, 2000, pp. 99–103.
URI:	http://wrap.warwick.ac.uk/id/eprint/5186