Infrared and visible image fusion based on NSCT and fuzzy logic
Infrared and visible image fusion based on NSCT and fuzzy logic
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DOI：
10.1109/icma.2010.5588318
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发表时间：
2010-10
期刊：
影响因子：
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通讯作者：
Songfeng Yin;Liangcai Cao;Qiaofeng Tan;Guofan Jin
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文献类型：
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作者：
Songfeng Yin;Liangcai Cao;Qiaofeng Tan;Guofan Jin
提出了一种基于非下采样轮廓波变换（NSCT）和模糊逻辑的新型红外（IR）和可见光图像融合方法。使用 NSCT 将输入的红外和可见图像分解为一系列低频和高频子带。红外图像低频子带中每个像素对背景和目标的隶属度是通过使用模糊逻辑来确定的。然后采用自适应加权平均作为低频子带系数的融合，同时对高频子带系数的融合执行最大绝对值选择。融合图像是通过对融合系数进行逆 NSCT 获得的。真实红外和可见光图像的实验结果表明，该方法有效增强了红外目标并保留了可见光图像的细节。
A novel infrared (IR) and visible image fusion method based on nonsubsampled contourlet transform (NSCT) and fuzzy logic is proposed. Input IR and visible images are decomposed into a series of low frequency and high frequency subbands by using NSCT. The degree of membership to the background and the target for each pixel in the low frequency subband of the IR image is determined by using fuzzy logic. An adaptive weighted average is then taken as the fusion of low frequency subband coefficients while maximum absolution selection is performed for the fusion of high frequency subband coefficients. The fused image is obtained by taking inverse NSCT of the fused coefficients. Experimental results with real IR and visible images show that the proposed method effectively enhances infrared targets and preserves details of the visible image.