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Pixel level multifocus image fusion based on variational decomposition in combination with structure tensor analysis

机译:基于变分分解结合结构张量分析的像素级多焦点图像融合

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An image fusion Algorithm based on variational decomposition and energy of edge is presented in this paper. Firstly, each source image is decomposed into a geometrical component and a textured component by applying Rudin-Osher-Fatemi (ROF) model in combination with Chambolle's projection algorithm. Secondly, the corresponding components are fused separately. For fusing the geometrical components, a weighted average method is adopted. To construct the textured component, a reconstruction algorithm of vector field based on structure tensor analysis is adopted. Finally, the sum of the fused composites is calculated to obtain the fused result. Experiments show that the proposed algorithm works well in multi focus image fusion.
机译:提出了一种基于变分分解和边缘能量的图像融合算法。首先,通过结合Ruambo-Osher-Fatemi(ROF)模型和Chambolle的投影算法,将每个源图像分解为几何成分和纹理成分。其次,将相应的组件分开融合。为了融合几何成分,采用了加权平均法。为了构造纹理分量,采用了基于结构张量分析的矢量场重构算法。最后,计算融合复合物的总和以获得融合结果。实验表明,该算法在多焦点图像融合中效果良好。

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