Multi-Focus Image Fusion Based on Pixel Significance Using Counterlet Transform
Abstract The objective of image fusion is to merge multiple sources of images together in such a way that the final representation contains higher amount of useful information than any input one.. In this paper, a weighted average fusion method is proposed. It depends on using weights that are...
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Al-Khwarizmi College of Engineering – University of Baghdad
2015
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oai:doaj.org-article:8f97973fda07423dbbf5b04dc64117772021-12-02T05:32:52ZMulti-Focus Image Fusion Based on Pixel Significance Using Counterlet Transform1818-11712312-0789https://doaj.org/article/8f97973fda07423dbbf5b04dc64117772015-06-01T00:00:00Zhttp://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/247https://doaj.org/toc/1818-1171https://doaj.org/toc/2312-0789 Abstract The objective of image fusion is to merge multiple sources of images together in such a way that the final representation contains higher amount of useful information than any input one.. In this paper, a weighted average fusion method is proposed. It depends on using weights that are extracted from source images using counterlet transform. The extraction method is done by making the approximated transformed coefficients equal to zero, then taking the inverse counterlet transform to get the details of the images to be fused. The performance of the proposed algorithm has been verified on several grey scale and color test images, and compared with some present methods. Keywords: image fusion, counterlet transform (CT), pixel significance, weighted average. Iman M.G. AlwanAl-Khwarizmi College of Engineering – University of BaghdadarticleKeywords: image fusion, counterlet transform (CT), pixel significance, weighted average.Chemical engineeringTP155-156Engineering (General). Civil engineering (General)TA1-2040ENAl-Khawarizmi Engineering Journal, Vol 11, Iss 3 (2015) |
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Keywords: image fusion, counterlet transform (CT), pixel significance, weighted average. Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040 |
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Keywords: image fusion, counterlet transform (CT), pixel significance, weighted average. Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040 Iman M.G. Alwan Multi-Focus Image Fusion Based on Pixel Significance Using Counterlet Transform |
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Abstract
The objective of image fusion is to merge multiple sources of images together in such a way that the final representation contains higher amount of useful information than any input one.. In this paper, a weighted average fusion method is proposed. It depends on using weights that are extracted from source images using counterlet transform. The extraction method is done by making the approximated transformed coefficients equal to zero, then taking the inverse counterlet transform to get the details of the images to be fused. The performance of the proposed algorithm has been verified on several grey scale and color test images, and compared with some present methods.
Keywords: image fusion, counterlet transform (CT), pixel significance, weighted average.
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format |
article |
author |
Iman M.G. Alwan |
author_facet |
Iman M.G. Alwan |
author_sort |
Iman M.G. Alwan |
title |
Multi-Focus Image Fusion Based on Pixel Significance Using Counterlet Transform |
title_short |
Multi-Focus Image Fusion Based on Pixel Significance Using Counterlet Transform |
title_full |
Multi-Focus Image Fusion Based on Pixel Significance Using Counterlet Transform |
title_fullStr |
Multi-Focus Image Fusion Based on Pixel Significance Using Counterlet Transform |
title_full_unstemmed |
Multi-Focus Image Fusion Based on Pixel Significance Using Counterlet Transform |
title_sort |
multi-focus image fusion based on pixel significance using counterlet transform |
publisher |
Al-Khwarizmi College of Engineering – University of Baghdad |
publishDate |
2015 |
url |
https://doaj.org/article/8f97973fda07423dbbf5b04dc6411777 |
work_keys_str_mv |
AT imanmgalwan multifocusimagefusionbasedonpixelsignificanceusingcounterlettransform |
_version_ |
1718400363792433152 |