Infrared and Visible Image Fusion via Fast Approximate Bilateral Filter and Local Energy Characteristics

Zongping Li,Wenxin Lei,Tingting Liao,Jianming Zhang,Xudong Li,Zhu Xiao

doi:10.1155/2021/3500116

Zongping Li, Wenxin Lei + Show 4 more

Open Access

https://doi.org/10.1155/2021/3500116

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Abstract

Image fusion is to effectively enhance the accuracy, stability, and comprehensiveness of information. Generally, infrared images lack enough background details to provide an accurate description of the target scene, while visible images are difficult to detect radiation under adverse conditions, such as low light. People hoped that the richness of image details can be improved by using effective fusion algorithms. In this paper, we propose an infrared and visible image fusion algorithm, aiming to overcome some common defects in the process of image fusion. Firstly, we use fast approximate bilateral filter to decompose the infrared image and visible image to obtain the small-scale layers, large-scale layer, and base layer. Then, the fused base layer is obtained based on local energy characteristics, which avoid information loss of traditional fusion rules. The fused small-scale layers are acquired by selecting the absolute maximum, and the fused large-scale layer is obtained by summation rule. Finally, the fused small-scale layers, large-scale layer, and base layer are merged to reconstruct the final fused image. Experimental results show that our method retains more detailed appearance information of the fused image and achieves good results in both qualitative and quantitative evaluations.

Highlights

With the popularity of infrared image applied in military surveillance [1], remote sensing [2], medical imaging [3], space exploration [4], and other fields, people pay more and more attention to the fusion of infrared and visible images. ere are some differences in the characteristics and imaging regulation of infrared and visible images
The visible image (VI) that captures reflected light has high spatial discrimination and legible detail texture information, whereas visible image is greatly affected by weather and has poor imaging effect in cloudy, rainy, and night environments
Our contributions are as follows: (1) We introduce a fast approximate bilateral filter to decompose the original infrared or visible image

Summary

Introduction

With the popularity of infrared image applied in military surveillance [1], remote sensing [2], medical imaging [3], space exploration [4], and other fields, people pay more and more attention to the fusion of infrared and visible images. ere are some differences in the characteristics and imaging regulation of infrared and visible images. Infrared image (IR) that captures thermal radiation has strong anti-interference capability and can operate all day without being affected by lighting conditions, but its contrast is low and its ability to distinguish details is poor. The visible image (VI) that captures reflected light has high spatial discrimination and legible detail texture information, whereas visible image is greatly affected by weather and has poor imaging effect in cloudy, rainy, and night environments. E existing fusion methods are effective, but there are some common problems, such as poor contrast, block effect, information distortion, and so on. To address these issues and get better fusion performance, a novel fusion algorithm based on fast approximate bilateral filter and local energy characteristics is developed.

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