A General Perceptual Infrared and Visible Image Fusion Framework Based on Linear Filter and Side Window Filtering Technology

Recently, edge-preserving filters have achieved great success in infrared (IR) and visible (VI) image fusion field. However, most edge-preserving filters are complex. In this paper, with the side window filtering technology by which most filters can improve their edge-preserving capabilities, we pro...

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Main Authors: Huibin Yan, Zhongmin Li
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8939390/
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spelling doaj-4e60360d3d1846fd864df68b9e6a5b292021-03-30T01:12:00ZengIEEEIEEE Access2169-35362020-01-0183029304110.1109/ACCESS.2019.29616268939390A General Perceptual Infrared and Visible Image Fusion Framework Based on Linear Filter and Side Window Filtering TechnologyHuibin Yan0https://orcid.org/0000-0001-8537-3532Zhongmin Li1https://orcid.org/0000-0003-0530-3484School of Information Engineering, Nanchang Hangkong University, Nanchang, ChinaSchool of Information Engineering, Nanchang Hangkong University, Nanchang, ChinaRecently, edge-preserving filters have achieved great success in infrared (IR) and visible (VI) image fusion field. However, most edge-preserving filters are complex. In this paper, with the side window filtering technology by which most filters can improve their edge-preserving capabilities, we propose a general perceptual IR and VI image fusion framework with simple linear filter. Firstly, the source images are decomposed into edge feature components, hybrid components and base components by using linear filter and its side window version. Then, these components are combined by max-absolute fusion rule and improved max-absolute fusion rule. Finally, the fused image is reconstructed by adding all the fused components. In our experiments, two popular linear filters, i.e., box filter and Gaussian filter, are used to verify the effectiveness of the proposed framework. Experimental results show that the proposed fusion framework can obtain better perceptual fusion results than compared methods.https://ieeexplore.ieee.org/document/8939390/Image fusionside window filteringlinear filterinfrared imagesvisible images
collection DOAJ
language English
format Article
sources DOAJ
author Huibin Yan
Zhongmin Li
spellingShingle Huibin Yan
Zhongmin Li
A General Perceptual Infrared and Visible Image Fusion Framework Based on Linear Filter and Side Window Filtering Technology
IEEE Access
Image fusion
side window filtering
linear filter
infrared images
visible images
author_facet Huibin Yan
Zhongmin Li
author_sort Huibin Yan
title A General Perceptual Infrared and Visible Image Fusion Framework Based on Linear Filter and Side Window Filtering Technology
title_short A General Perceptual Infrared and Visible Image Fusion Framework Based on Linear Filter and Side Window Filtering Technology
title_full A General Perceptual Infrared and Visible Image Fusion Framework Based on Linear Filter and Side Window Filtering Technology
title_fullStr A General Perceptual Infrared and Visible Image Fusion Framework Based on Linear Filter and Side Window Filtering Technology
title_full_unstemmed A General Perceptual Infrared and Visible Image Fusion Framework Based on Linear Filter and Side Window Filtering Technology
title_sort general perceptual infrared and visible image fusion framework based on linear filter and side window filtering technology
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description Recently, edge-preserving filters have achieved great success in infrared (IR) and visible (VI) image fusion field. However, most edge-preserving filters are complex. In this paper, with the side window filtering technology by which most filters can improve their edge-preserving capabilities, we propose a general perceptual IR and VI image fusion framework with simple linear filter. Firstly, the source images are decomposed into edge feature components, hybrid components and base components by using linear filter and its side window version. Then, these components are combined by max-absolute fusion rule and improved max-absolute fusion rule. Finally, the fused image is reconstructed by adding all the fused components. In our experiments, two popular linear filters, i.e., box filter and Gaussian filter, are used to verify the effectiveness of the proposed framework. Experimental results show that the proposed fusion framework can obtain better perceptual fusion results than compared methods.
topic Image fusion
side window filtering
linear filter
infrared images
visible images
url https://ieeexplore.ieee.org/document/8939390/
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