28 April 2021 Infrared and visible-image fusion using multiscale visual saliency extraction based on spatial weight matrix
Xiaohui Wu, Jufeng Zhao, Haifeng Mao, Guangmang Cui
Author Affiliations +
Abstract

We propose a dual-band fusion method using multiscale visual saliency extraction based on spatial weight matrix. There are two main contributions in this paper. The first major contribution is to use the local window based on the gray distance of the spatial weight for saliency extraction. Second, to emphasize those potential targets and details with different sizes from source images, we based on the saliency extraction method of multi-window and fusion of different scales to achieve the preservation of more information. The proposed method is mainly divided into four steps. First, we use a spatial weight matrix of different window sizes to enhance targets of different sizes in the image. Then, through the different processing of each enhanced image to get detailed images, we use a special method to fuse the obtained details of each scale. Then, reconstruct the results obtained at each scale. Finally, we have the exact weight index selection to get better fusion results. This method solves the problem of improper weight selection and the result deteriorates. Through comparison and verification, our results retain more detailed information from the original images.

© 2021 SPIE and IS&T 1017-9909/2021/$28.00© 2021 SPIE and IS&T
Xiaohui Wu, Jufeng Zhao, Haifeng Mao, and Guangmang Cui "Infrared and visible-image fusion using multiscale visual saliency extraction based on spatial weight matrix," Journal of Electronic Imaging 30(2), 023029 (28 April 2021). https://doi.org/10.1117/1.JEI.30.2.023029
Received: 26 January 2021; Accepted: 2 April 2021; Published: 28 April 2021
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Image fusion

Infrared imaging

Infrared radiation

Visualization

Visible radiation

Detection and tracking algorithms

Single crystal X-ray diffraction

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