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http://dx.doi.org/10.3745/JIPS.02.0166

A Noisy Infrared and Visible Light Image Fusion Algorithm  

Shen, Yu (School of Electronic and Information Engineering, Lanzhou Jiaotong University)
Xiang, Keyun (School of Electronic and Information Engineering, Lanzhou Jiaotong University)
Chen, Xiaopeng (School of Electronic and Information Engineering, Lanzhou Jiaotong University)
Liu, Cheng (School of Electronic and Information Engineering, Lanzhou Jiaotong University)
Publication Information
Journal of Information Processing Systems / v.17, no.5, 2021 , pp. 1004-1019 More about this Journal
Abstract
To solve the problems of the low image contrast, fuzzy edge details and edge details missing in noisy image fusion, this study proposes a noisy infrared and visible light image fusion algorithm based on non-subsample contourlet transform (NSCT) and an improved bilateral filter, which uses NSCT to decompose an image into a low-frequency component and high-frequency component. High-frequency noise and edge information are mainly distributed in the high-frequency component, and the improved bilateral filtering method is used to process the high-frequency component of two images, filtering the noise of the images and calculating the image detail of the infrared image's high-frequency component. It can extract the edge details of the infrared image and visible image as much as possible by superimposing the high-frequency component of infrared image and visible image. At the same time, edge information is enhanced and the visual effect is clearer. For the fusion rule of low-frequency coefficient, the local area standard variance coefficient method is adopted. At last, we decompose the high- and low-frequency coefficient to obtain the fusion image according to the inverse transformation of NSCT. The fusion results show that the edge, contour, texture and other details are maintained and enhanced while the noise is filtered, and the fusion image with a clear edge is obtained. The algorithm could better filter noise and obtain clear fused images in noisy infrared and visible light image fusion.
Keywords
Bilateral Filter; Image Fusion; Local Area Standard Variance; Nonsubsample Contourlet Transform (NSCT);
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