基于NSCT和模糊逻辑的红外与可见光图像融合

Songfeng Yin, Liangcai Cao, Qiaofeng Tan, Guofan Jin
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引用次数: 30

摘要

提出了一种基于非下采样轮廓波变换(NSCT)和模糊逻辑的红外图像与可见光图像融合方法。利用NSCT将输入的红外和可见光图像分解为一系列低频和高频子带。利用模糊逻辑确定红外图像低频子带各像素点与背景和目标的隶属度。低频子带系数融合采用自适应加权平均,高频子带系数融合采用最大绝对值选择。通过对融合系数进行NSCT逆变换得到融合图像。实际红外和可见光图像的实验结果表明,该方法在有效增强红外目标的同时,保留了可见光图像的细节。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Infrared and visible image fusion based on NSCT and fuzzy logic
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.
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