基于分数阶微分的多尺度多聚焦图像融合.

Aiming at multi-focus image fusion, the complementary information at each scale is fused in a targeted manner using a multi-scale fusion method. First, the source image is decomposed into a background layer and a detail layer using the L0 gradient minimization smoothing method, and then a fractional-order edge detection mask is used to preserve the edge information in the background layer, and a fractional-order gradient energy operator is introduced in the detail layer for weight assignment. The experimental results show that the proposed fractional-order gradient energy operator is more sensitive than the integer-order gradient energy clarity operator, which is consistent with the human visual perception. The fusion method proposed effectively avoids artifacts and block effects in the fused images, and retains the source image information more fully. [ABSTRACT FROM AUTHOR]