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Multi-scale transforms (MST)-based methods are popular for multi-focus image fusion recently because of the superior performances, such as the fused image containing more details of edges and textures. However, most of MST-based methods are based on pixel operations, which require a large amount of data processing. Moreover, different fusion strategies cannot completely preserve the clear pixels within the focused area of the source image to obtain the fusion image. To solve these problems, this paper proposes a novel image fusion method based on focus-region-level partition and pulse-coupled neural network (PCNN) in nonsubsampled contourlet transform (NSCT) domain. A clarity evaluation function is constructed to measure which regions in the source image are focused. By removing the focused regions from the source images, the non-focus regions which contain the edge pixels of the …