摘要
红外与可见光图像融合旨在生成一幅新的图像,能够对场景进行更全面的描述。本文提出一种图像多尺度混合信息分解方法,可有效提取代表可见光特征分量的纹理细节信息和代表红外特征分量的边缘信息。本文方法将边缘信息进行进一步分割以确定各分解子信息的融合权重,以有效地将多尺度红外光谱特征注入到可见光图像中,同时保留可见光图像中重要的场景细节信息。实验结果表明,本文方法能够有效提取图像中的红外目标,实现在融合图像中凸显红外目标的同时保留尽可能多的可见光纹理细节信息,无论是主观视觉还是客观评价指标都优于现有的图像融合方法。
Infrared and visible image fusion is designed to generate a fused image that provides a more complete description of the scene.In this paper,a novel multi-scale hybrid image decomposition algorithm is proposed,which can effectively extract the small-scale texture detail information of the visible image and the large-scale edge information of the infrared image.The large-scale edge image of the infrared image is used to be segmented and construct the fused weights,which can not only inject the multi-scale infrared spectrum into the visible image effectively,but also preserve the details of the scenes in the visible image.Experimental results show that the proposed algorithm can obtain state-of-the-art performance both in subjective and objective evaluation.
作者
荣传振
贾永兴
吴城
杨宇
朱莹
Rong Chuanzhen;Jia Yongxing;Wu Cheng;Yang Yu;Zhu Ying(Communications Engineering College,Army Engineering University of PLA,Nanjing,210007,China;Information Communications College,National University of Defense Technology,Xi'an,710106,China)
出处
《数据采集与处理》
CSCD
北大核心
2019年第1期146-156,共11页
Journal of Data Acquisition and Processing
基金
江苏省自然科学基金(BK2012511)资助项目
陆军工程大学预研基金(2014-4-07
2016-5-06)资助项目
关键词
多尺度混合信息分解
引导滤波
高斯滤波
图像融合
hybrid multi-scale decomposition
image guided filtering
Gaussian filter
image fusion
