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Reseach Article

Innovative Multilevel Image Fusion Algorithm using Combination of Transform Domain and Spatial Domain Methods with Comparative Analysis of Wavelet and Curvelet Transform

by Roshna J Sapkal, Sunita M Kulkarni
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 66 - Number 21
Year of Publication: 2013
Authors: Roshna J Sapkal, Sunita M Kulkarni
10.5120/11244-6478

Roshna J Sapkal, Sunita M Kulkarni . Innovative Multilevel Image Fusion Algorithm using Combination of Transform Domain and Spatial Domain Methods with Comparative Analysis of Wavelet and Curvelet Transform. International Journal of Computer Applications. 66, 21 ( March 2013), 41-47. DOI=10.5120/11244-6478

@article{ 10.5120/11244-6478,
author = { Roshna J Sapkal, Sunita M Kulkarni },
title = { Innovative Multilevel Image Fusion Algorithm using Combination of Transform Domain and Spatial Domain Methods with Comparative Analysis of Wavelet and Curvelet Transform },
journal = { International Journal of Computer Applications },
issue_date = { March 2013 },
volume = { 66 },
number = { 21 },
month = { March },
year = { 2013 },
issn = { 0975-8887 },
pages = { 41-47 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume66/number21/11244-6478/ },
doi = { 10.5120/11244-6478 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:23:04.548597+05:30
%A Roshna J Sapkal
%A Sunita M Kulkarni
%T Innovative Multilevel Image Fusion Algorithm using Combination of Transform Domain and Spatial Domain Methods with Comparative Analysis of Wavelet and Curvelet Transform
%J International Journal of Computer Applications
%@ 0975-8887
%V 66
%N 21
%P 41-47
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image fusion is widely used term in different applications namely satellite imaging, remote sensing, multifocus imaging and medical imaging. In this paper, we have implemented multi level image fusion in which fusion is carried out in two stages. Firstly, Discrete wavelet or Fast Discrete Curvelet transform is applied on both source images and secondly image fusion is carried out with either spatial domain methods like Averaging, Minimum selection, maximum selection and PCA or with Pyramid transform methods like Laplacian Pyramid transform. Further, comparative analysis of fused image obtained from both Discrete Wavelet and Fast Discrete Curvelet transform is done which proves effective image fusion using proposed Curvelet transform than Wavelet transform through enhanced visual quality of fused image and by analysis of 7 quality metrics parameters. The proposed method is very innovative which can be applied to medical and multifocus imaging applications in real time. These analyses can be useful for further research work in image fusion and also the fused image obtained using Curvelet transform can be helpful for better medical diagnosis.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Averaging AG Cc CT Discrete Wavelet Transform E Fast Discrete Curvelet Transform Image fusion Image Quality Metrics Laplacian Pyramid Maximum Selection Minimum Selection MRI PCA PSNR RMSE SD