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Reseach Article

A New Image Fusion Method based on Integration of Wavelet and Fast Discrete Curvelet Transform

by Anjali A. Pure, Neelesh Gupta, Meha Shrivastava
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 69 - Number 18
Year of Publication: 2013
Authors: Anjali A. Pure, Neelesh Gupta, Meha Shrivastava
10.5120/12073-8217

Anjali A. Pure, Neelesh Gupta, Meha Shrivastava . A New Image Fusion Method based on Integration of Wavelet and Fast Discrete Curvelet Transform. International Journal of Computer Applications. 69, 18 ( May 2013), 31-35. DOI=10.5120/12073-8217

@article{ 10.5120/12073-8217,
author = { Anjali A. Pure, Neelesh Gupta, Meha Shrivastava },
title = { A New Image Fusion Method based on Integration of Wavelet and Fast Discrete Curvelet Transform },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 69 },
number = { 18 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 31-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume69/number18/12073-8217/ },
doi = { 10.5120/12073-8217 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:30:37.896506+05:30
%A Anjali A. Pure
%A Neelesh Gupta
%A Meha Shrivastava
%T A New Image Fusion Method based on Integration of Wavelet and Fast Discrete Curvelet Transform
%J International Journal of Computer Applications
%@ 0975-8887
%V 69
%N 18
%P 31-35
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image fusion is one of the most useful term related to digital image processing, computer vision and medical imaging. The objective of image fusion is to extract the useful information from several images into a single image. Recently, more research has been done on wavelet based image fusion methods for medical application. Wavelet transform is useful for objects with point singularities and analyses the feature of images in detailed, but it does not provide information about edges clearly. While curvelet transform is more useful for the analysis of images having curved shape edges. So, in this paper, a new image fusion method is proposed based on the integration of wavelet and fast discrete curvelet transform, which describe the curved shapes of images and analyses feature of images better. This paper uses MRI and CT images for fusion which contains complementary information helpful for diagnosis of disease. The fusion results obtained from proposed method are analyzed and compared visually and statistically with different types of wavelets used in image fusion. The results of proposed method are efficient and improve the Entropy, PSNR, Mean, STD and MSE. The proposed method can be helpful for better medical diagnosis.

References
  1. Shih-Gu Huang, Wavelet for Image Fusion.
  2. Smt. G. Mamatha, L. Gayatri, 'AN IMAGE FUSION USING WAVELET AND CURVELET TRANSFORMS', Global Journal of Advanced EngineeringTechnologies,Vol1,Issue-2,2012,ISSN:2277-6370.
  3. A. Soma Sekhar, Dr. M. N. GiriPrasad, 'A Novel Approach of Image Fusion on MR and CT Images Using Wavelet Transforms, IEEE 2011.
  4. S. Bharath and E. S. Karthik Kumar, Implementation Of Image Fusion Algorithm Using 2gcurvelet Transforms, ISBN 978-1-4675-2248-9@2012.
  5. Bin Yang and Shutao Li, Multifocus Image Fusion and Restoration with Sparse Representation, IEEE 2010.
  6. Emmanuel Cand`es, Laurent Demanet, David Donoho and Lexing Ying; Fast Discrete Curvelet Transforms, Applied and Computational Mathematics, Caltech Pasadena 2006.
  7. Jianwei Ma and Gerlind Plonka, The Curvelet Transform, IEEE SIGNAL PROCESSING MAGAZINE
  8. MARCH 2010.
  9. Gang Hong, Yun Zhang, 'The effect of different types of wavelets on image fusion.
  10. Deepa M, Wavelet and Curvelet Based Thresholding Techniques for Image Denoising, IJARCSEE vol1 Issue2012, ISSN: 227-9043.
  11. E. J. Candes, D. L. Donoho Curvelets: A Surprisingly Effective Nonadaptive Representation for Objects with Edges.
  12. M. Sifuzzaman M. R. Islam, M. Z. Ali, Application Of Wavelet and its Advantages Compared to Fourier Transform, Journal of Physical Science,Vol. 13,2009,121-134,ISSN:0972-8791.
  13. Y. Kiran Kumar, Comparison of Fusion Techniques Applied to preclinical images: Fast Discrete Curvelet Transform using Wrapping Technique & Wavelet Transform, JATIT2009.
  14. Pao-Yen Lin, An introduction wavelet transforms.
  15. Myungjin Choi, Rae Young Kim, Moon-GyuKim, 'The curvelet transform for image fusion.
  16. Rafael C. Gonzalez and Richard E. Woods, Digital image Processing, Third Edition.
Index Terms

Computer Science
Information Sciences

Keywords

Image fusion MRI Image CT image Discrete Wavelet Transform (DWT) Fast Discrete Curvelet Transform (FDCT)