Multi sensor image fusion enhances the human visual perception and machine interpretation of the scene by integrating complementary and redundant information given by multi sensor data. In this paper, we proposed a multi sensor image fusion method that provides a high contrast fused image having no structural bias and which is more robust to different types of source images. These objectives are achieved through an intelligent ensemble of guided image filter, nonsubsampled shearlet transform, texture energy measures, and morphological operations. The proposed method is validated on medical, infrared-visible, and multi focus images. The qualitative and quantitative assessment proved the superiority of the proposed method compared to state of the art image fusion methods.

中文翻译：

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基于引导图像滤波器和NSST的对比度增强的多传感器图像融合

多传感器图像融合通过整合多传感器数据给出的互补和冗余信息来增强人类对场景的视觉感知和机器解释。在本文中，我们提出了一种多传感器图像融合方法，该方法提供了一种没有结构偏差的高对比度融合图像，并且对不同类型的源图像具有更强的鲁棒性。这些目标是通过引导图像​​过滤器、非下采样剪切波变换、纹理能量测量和形态学操作的智能集成来实现的。所提出的方法在医学、红外可见光和多焦点图像上得到了验证。定性和定量评估证明了所提出的方法与最先进的图像融合方法相比的优越性。