基于划区域宇宙算法的红外与可见光图像融合研究
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(黄淮学院 智能制造学院,河南 驻马店 463000)

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张 健 (1980-),男,硕士,副教授,主要从事物联网技术应用等方面的研究。

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TP391.41

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河南省科技发展计划项目(212102210515)资助项目


Infrared and visible image fusion based on divide region universe algorithm
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(School of Intelligent Manufacturing, Huanghuai University, Zhumadian, Henan 463000, China)

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    摘要:

    为了克服红外与可见光图像融合过程中目标物体边缘处产生虚影的问题,提出划区域宇宙算法(divide region universe algorithm,DRUA) 。首先建立宇宙空间模型,核心区域的宇宙可进行双向交流,非核心区域的宇宙只能进行单向交流;接着连接核心区域与非核心区域的连接宇宙能够使得核心区域与非核心区域形成邻居关系;然后红外与可见光图像分别获得细节图层、基础图层、显著图层,不同层使用不同融合策略;最后给出了宇宙优化融合的流程。实验仿真表明,本文算法融合图像结果具有较多的热目标、场景信息,视觉效果符合人眼的视觉特征,互信息、标准 差、空间频率、平均梯度指标相比其他算法提升平均值分别为17.57%、14.80%、34.16%、21.01%,优于其他算法。

    Abstract:

    In order to overcome the problem of phantom shadow at the edge of the object in the process of infrared and visible image fusion,an image fusion method based on divide region universe algorithm (DRUA) is proposed.Firstly,the space model of the universe is established,the universe in the core region is communicated with each other bilaterally,and the universe in the non-core region is only communicated with each other unilaterally.Secondly,the connected universe connecting the core region and the non-core region forms a neighborhood relationship between the core region and the non-core region.Thirdly,the detail layer,the basic layer and the saliency layer of the infrared and visible images are obtained respectively,and different fusion strategies are used for different layers.Finally,the fusion process of universe optimization is given.Experimental results show that the proposed method has more thermal target and scene information,and the visual effect is consistent with the visual characteristics of the human eye.Compared with other algorithms, the mutual information, standard deviation,spatial frequency,and average gradient index are increased by 17.57%,14.80%,34.16% and 21.01%,respectively,so that it is better than other algorithms.

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张健,黄安穴.基于划区域宇宙算法的红外与可见光图像融合研究[J].光电子激光,2024,35(9):962~970

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  • 收稿日期:2023-04-08
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  • 在线发布日期: 2024-08-19
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