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Reseach Article

Comparative Evaluation of DWT and DT-CWT for Image Fusion and De-noising

by Rudra Pratap Singh Chauhan, Rajiva Dwivedi, Sandeep Negi
International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 4 - Number 2
Year of Publication: 2012
Authors: Rudra Pratap Singh Chauhan, Rajiva Dwivedi, Sandeep Negi
10.5120/ijais12-450662

Rudra Pratap Singh Chauhan, Rajiva Dwivedi, Sandeep Negi . Comparative Evaluation of DWT and DT-CWT for Image Fusion and De-noising. International Journal of Applied Information Systems. 4, 2 ( September 2012), 40-45. DOI=10.5120/ijais12-450662

@article{ 10.5120/ijais12-450662,
author = { Rudra Pratap Singh Chauhan, Rajiva Dwivedi, Sandeep Negi },
title = { Comparative Evaluation of DWT and DT-CWT for Image Fusion and De-noising },
journal = { International Journal of Applied Information Systems },
issue_date = { September 2012 },
volume = { 4 },
number = { 2 },
month = { September },
year = { 2012 },
issn = { 2249-0868 },
pages = { 40-45 },
numpages = {9},
url = { https://www.ijais.org/archives/volume4/number2/275-0662/ },
doi = { 10.5120/ijais12-450662 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T10:46:59.566479+05:30
%A Rudra Pratap Singh Chauhan
%A Rajiva Dwivedi
%A Sandeep Negi
%T Comparative Evaluation of DWT and DT-CWT for Image Fusion and De-noising
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 4
%N 2
%P 40-45
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In various real life applications such as remote sensing and medical image diagnosis, image fusion plays imperative role and it is more popular for image processing applications. Because of inadequate nature of practical imaging systems the capture images or acquired images are corrupted from various noise hence fusion of image is an integrated approach where reduction of noise and retaining the original features of image is essential. Image fusion is the process of extracting meaningful visual information from two or more images and combining them to form one fused image. Discrete Wavelet Transform (DWT) has a wide range of application in fusion of noise images. Previously, real valued wavelet transforms have been used for image fusion. Although this technique has provided improvements over more inhabitant methods, this transform suffers from the shift variance and lack of directionality associated with its wavelet bases. These problems have been overcome by the use of a reversible and discrete complex wavelet transform (the Dual Tree Complex Wavelet Transform DT-CWT). This paper therefore introduces an alternative structure such as DT-CWT that is more flexible, highly directional and shift invariant which outperforms the conventional method in terms of PSNR and image quality improvement.

References
  1. {Chipman et al. 1995} Chipman, L. J. , Orr, T. M. , and Lewis, L. N. (1995). Wavelets and image fusion. In Proceedings IEEE International Conference on Image Processing, Washigton D. C. , volume 3, pages 248-251. IEEE.
  2. N. G. Kingsbury, "The dual-tree complex wavelet transform with improved orthogonality and symmetry properties", IEEE international Conference on Image processing, pages 375-378, September 2000.
  3. N. G. Kingsbury, "The dual-tree complex wavelet transform: a new technique for shift invariance and directional filters, IEEE Digital Signal Processing Workshop, 1998.
  4. S. M. Mahbubur Rahman, M. Omair Ahmad and M. N. S Swamy, "Constant-based fusion of noisy image using discrete wavelet transform", IET Image Process, 2010, Vol. 4 Iss. 5, pp. 374-384 doi:10. 1049/ iet-ipr. 20009. 0163.
  5. Koren, I. and Laine, A. (1998). A discrete dyadic wavelet transform for multidimensional feature analysis. In Akay, M,, editor, Time Frequency and Wavelets in Biomedical Signal Processing, pages 425-449. IEEE Press.
  6. Koren, I. and Laine, A. and Tylor, F. (1995). Image fusion using steerable dyadic wavelet transforms. In proceedings IEEE International Conference on Image Processing, Washington D. C. , pages 232-235. IEEE.
  7. Resources for research in image fusion :[Online], http://www. imagefusion. org/
  8. The Math works, 'Wavelet Toolbox (ver 5) User's guide', 2007, URL: www. mathworks. com
  9. H. B. Mitchell. Image Fusion theories, techniques, and applications", ISBN 978-642-11215-7, Springer-Verlag Berlin Heidelberg, 2010.
  10. Kingsbury, N. G. (2000) "A dual-tree complex wavelet transform with improved orthogonality and symmetry properties. Proc. IEEE Conf. on Image Processing, Vancouver, September 11-13, 2000, (paper 1429).
  11. Nikolov, S. G. , Bull, D. R. , Canagarajah, C. N. , Halliwell, M. and Wells, P. N. T. (2000), 2-D image fusion by multiscale edge graph combination. In 3rd International Conference on Information Fusion (Fusion 2000), Paris, France, 10-13 July, volume I, pages MoD3-16-22. International Society of Information Fusion (ISIF).
  12. Zhang, Z. and Blum, R. (1999). A categorization of multiscale-decomposition-based image fusion schemes with a performance study for a digital camera application. Proceedings of the IEEE. Pages 1315-1328.
Index Terms

Computer Science
Information Sciences

Keywords

Wavelet transform Discrete Wavelet Transform (DWT) Dual-Tree Complex Wavelet Transform (DT-CWT) Image Fusion