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Contrast Enhanced Multi Sensor Image Fusion Based on Guided Image Filter and NSST

机译:基于引导图像滤波器和NSST的对比增强多传感器图像融合

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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.
机译:多传感器图像融合通过集成多传感器数据给出的互补和冗余信息来增强场景的人类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,其提供没有结构偏压的高对比度融合图像,并且对不同类型的源图像更鲁棒。 这些目标是通过引导图像过滤器的智能集合来实现的,非法采样的Shearlet变换,纹理能量测量和形态学操作。 所提出的方法在医疗,红外可见和多重焦点图像上验证。 定性和定量评估证明了与艺术图像融合方法的状态相比所提出的方法的优势。

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