计算机科学 ›› 2020, Vol. 47 ›› Issue (3): 124-129.doi: 10.11896/jsjkx.190100038
朱莹,夏亦犁,裴文江
ZHU Ying,XIA Yi-li,PEI Wen-jiang
摘要： 将红外图像与可见光图像融合在一起,可增强视觉效果,使人产生更完整的场景感知。基于二维经验模态分解(Bidimensional Empirical Mode Decomposition,BEMD)的图像融合方法运行时间较长,因此,文中提出了一种基于改进的二维经验模态分解的红外与可见光图像快速自适应融合方法,采用顺序统计滤波器和高斯滤波器直接生成均值包络曲面,从而加速图像的分解过程。首先,将可见光图像转化到HIS(Hue-Intensity-Saturation)颜色空间;然后,用改进的BEMD对强度分量I和红外图像进行分解,生成高频分量和低频分量,高频分量和低频分量分别采用自适应局部加权融合规则和算术平均融合规则;最后,将强度分量I与红外图像的融合结果图经过逆HIS变换到RGB颜色空间,从而得到融合图像。仿真实验表明,该融合算法不仅运行速度快,而且融合效果最佳,最大程度地保留了红外图像的边缘细节特征和可见光图像的光谱信息。
中图分类号:
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