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Infrared and Visible Image Fusion Based on Nonlinear Enhancement and NSST Decomposition
Xiaoxue XING
Changchun University
Corresponding Author
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This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at EURASIP Journal on Wireless Communications and Networking.
In Multi-scale Geometric Analysis (MGA)-based fusion methods for infrared and visible images, adopting the same representation for the two types of the images will result in the non-obvious thermal radiation target in the fused image, which can hardly be distinguished from the background. To solve the problem, a novel fusion algorithm based on nonlinear enhancement and Non-Subsampled Shearlet Transform (NSST) decomposition is proposed. Firstly, NSST is used to decompose the two source images into low- and high-frequency sub-bands. Then, the Wavelet Transform (WT) is used to decompose high-frequency sub-bands into obtain approximate sub-bands and directional detail sub-bands. The “average” fusion rule is performed for fusion for approximate sub-bands. And the “max-absolute” fusion rule is performed for fusion for directional detail sub-bands. The inverse WT is used to reconstruct the high-frequency sub-bands. To highlight the thermal radiation target, we construct a non-linear transform function to determine the fusion weight of low-frequency sub-bands, and whose parameters can be further adjusted to meet different fusion requirements. Finally, the inverse NSST is used to reconstruct the fused image. The experimental results show that the proposed method can simultaneously enhance the thermal target in infrared images and preserve the texture details in visible images, and which is competitive with or even superior to the state-of-the-art fusion methods in terms of both visual and quantitative evaluations.
Keywords
Image Fusion, Non-sampled Shearlet Transform, Infrared and Visible Image, Nonlinear Enhancement, Fusion Weight
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Peer Review Timeline
CURRENT STATUS: Published
Version 2
Posted 14 May, 2020
Published
On 24 Aug, 2020
No community comments so far
Editorial decision: Accept
On 02 Aug, 2020
Review #2 received
Received 20 May, 2020
Reviewer #2 agreed
On 18 May, 2020
Review #1 received
Received 17 May, 2020
Reviewer #1 agreed
On 15 May, 2020
Reviewers invited
Invitations sent on 14 May, 2020
Editor assigned
On 30 Apr, 2020
Submission checks complete
On 29 Apr, 2020
Editor invited
On 29 Apr, 2020
No comments provided
Editorial decision: Minor revision
On 21 Apr, 2020
Review #2 received
Received 19 Apr, 2020
Reviewer #2 agreed
On 10 Mar, 2020
Reviewer #1 agreed
On 08 Mar, 2020
Review #1 received
Received 08 Mar, 2020
Reviewers invited
Invitations sent on 07 Mar, 2020
Editor assigned
On 27 Feb, 2020
Editor invited
On 26 Feb, 2020
Submission checks complete
On 26 Feb, 2020
First submitted
On 20 Feb, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Systems and Networking
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This preprint is under consideration at EURASIP Journal on Wireless Communications and Networking. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Infrared and Visible Image Fusion Based on Nonlinear Enhancement and NSST Decomposition
Xiaoxue XING
Changchun University
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
Version 2
Posted 14 May, 2020
Published
On 24 Aug, 2020
No community comments so far
Editorial decision: Accept
On 02 Aug, 2020
Review #2 received
Received 20 May, 2020
Reviewer #2 agreed
On 18 May, 2020
Review #1 received
Received 17 May, 2020
Reviewer #1 agreed
On 15 May, 2020
Reviewers invited
Invitations sent on 14 May, 2020
Editor assigned
On 30 Apr, 2020
Submission checks complete
On 29 Apr, 2020
Editor invited
On 29 Apr, 2020
No comments provided
Editorial decision: Minor revision
On 21 Apr, 2020
Review #2 received
Received 19 Apr, 2020
Reviewer #2 agreed
On 10 Mar, 2020
Reviewer #1 agreed
On 08 Mar, 2020
Review #1 received
Received 08 Mar, 2020
Reviewers invited
Invitations sent on 07 Mar, 2020
Editor assigned
On 27 Feb, 2020
Editor invited
On 26 Feb, 2020
Submission checks complete
On 26 Feb, 2020
First submitted
On 20 Feb, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Systems and Networking
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at EURASIP Journal on Wireless Communications and Networking.
In Multi-scale Geometric Analysis (MGA)-based fusion methods for infrared and visible images, adopting the same representation for the two types of the images will result in the non-obvious thermal radiation target in the fused image, which can hardly be distinguished from the background. To solve the problem, a novel fusion algorithm based on nonlinear enhancement and Non-Subsampled Shearlet Transform (NSST) decomposition is proposed. Firstly, NSST is used to decompose the two source images into low- and high-frequency sub-bands. Then, the Wavelet Transform (WT) is used to decompose high-frequency sub-bands into obtain approximate sub-bands and directional detail sub-bands. The “average” fusion rule is performed for fusion for approximate sub-bands. And the “max-absolute” fusion rule is performed for fusion for directional detail sub-bands. The inverse WT is used to reconstruct the high-frequency sub-bands. To highlight the thermal radiation target, we construct a non-linear transform function to determine the fusion weight of low-frequency sub-bands, and whose parameters can be further adjusted to meet different fusion requirements. Finally, the inverse NSST is used to reconstruct the fused image. The experimental results show that the proposed method can simultaneously enhance the thermal target in infrared images and preserve the texture details in visible images, and which is competitive with or even superior to the state-of-the-art fusion methods in terms of both visual and quantitative evaluations.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.