RGB-NIR image fusion
Image processing techniques, such as linear filters and non-linear filters were studied and gaussian filter was used. Various Convolutional Neural Networks variants were also introduced and evaluated based on their ability in feature extraction. A pre-trained VGG-19 network using ImageNet weig...
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/148972 |
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sg-ntu-dr.10356-1489722023-07-07T17:19:02Z RGB-NIR image fusion Pan, Liangyi Lap-Pui Chau School of Electrical and Electronic Engineering elpchau@ntu.edu.sg Engineering::Electrical and electronic engineering::Computer hardware, software and systems Image processing techniques, such as linear filters and non-linear filters were studied and gaussian filter was used. Various Convolutional Neural Networks variants were also introduced and evaluated based on their ability in feature extraction. A pre-trained VGG-19 network using ImageNet weights was chosen for this project. Past Image Fusion methods were also studied. A fusion strategy was then proposed. Lastly, the proposed solution was evaluated against other image fusion methods using several quality metrics, where the proposed solution showed positive results on par with more recent methods such as DenseFuse and IFCNN Bachelor of Engineering (Electrical and Electronic Engineering) 2021-05-21T11:35:10Z 2021-05-21T11:35:10Z 2021 Final Year Project (FYP) Pan, L. (2021). RGB-NIR image fusion. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/148972 https://hdl.handle.net/10356/148972 en B3039-201 application/pdf Nanyang Technological University |
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Nanyang Technological University |
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NTU Library |
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Asia |
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Singapore Singapore |
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NTU Library |
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English |
| topic |
Engineering::Electrical and electronic engineering::Computer hardware, software and systems |
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Engineering::Electrical and electronic engineering::Computer hardware, software and systems Pan, Liangyi RGB-NIR image fusion |
| description |
Image processing techniques, such as linear filters and non-linear filters were studied and
gaussian filter was used. Various Convolutional Neural Networks variants were also
introduced and evaluated based on their ability in feature extraction. A pre-trained
VGG-19 network using ImageNet weights was chosen for this project. Past Image Fusion
methods were also studied. A fusion strategy was then proposed. Lastly, the proposed
solution was evaluated against other image fusion methods using several quality metrics,
where the proposed solution showed positive results on par with more recent methods
such as DenseFuse and IFCNN |
| author2 |
Lap-Pui Chau |
| author_facet |
Lap-Pui Chau Pan, Liangyi |
| format |
Final Year Project |
| author |
Pan, Liangyi |
| author_sort |
Pan, Liangyi |
| title |
RGB-NIR image fusion |
| title_short |
RGB-NIR image fusion |
| title_full |
RGB-NIR image fusion |
| title_fullStr |
RGB-NIR image fusion |
| title_full_unstemmed |
RGB-NIR image fusion |
| title_sort |
rgb-nir image fusion |
| publisher |
Nanyang Technological University |
| publishDate |
2021 |
| url |
https://hdl.handle.net/10356/148972 |
| _version_ |
1772828924699475968 |