Infrared and Visible Image Fusion based on a Dual-Channel Spiking Cortical Model via LatLRR for Micro CNC engraving milling machine Intelligent knife setting

Xigui Zheng  ^1,2

¹School of Mechanical Engineering, Zhengzhou University of Science and Technology Zhengzhou 450000,China
²Henan Digital Intelligent Equipment Engineering Research Center

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Received: December 12, 2020
Accepted: May 17, 2021
Publication Date: June 24, 2021

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: RIS|BibTeX|https://doi.org/10.6180/jase.202112_24(6).0017  

ABSTRACT

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In the traditional infrared and visible image fusion algorithms, there are some problems such as week target, missing background, blur edge information and so on. Therefore, we propose a new infrared and visible image fusion algorithm based on a dual-channel spiking cortical model (DCSCM) via LatLRR in this paper. First, a non-down-sampling shearlet transform (NSST) is applied to the source image to ob-tain the corresponding low-frequency and high-frequency components. Then, the LatLRR method and DCSCM model are used to fuse the low and high frequency component, respectively. Finally, NSST in-verse transformation is performed for the fused components to obtain the final fused image. Compared with other state-of-the-art methods, the experiment results on different scenarios show that the pro-posed algorithm has better visual effect, and higher objective evaluation values. And it can play an im-portant role in Micro CNC engraving milling machine intelligent knife setting.

Keywords: Infrared and visible image fusion, dual-channel spiking cortical model, LatLRR, NSST, machine intelli-gent