基于分数阶微分的多尺度多聚焦图像融合

Multi-focus Image Fusion with Multi-scale Based on Fractional Order Differentiation

针对多聚焦图像融合问题,借鉴多尺度融合方法对各个尺度的互补信息进行针对性融合.首先,运用L 0梯度最小化的平滑方法将源图像分解为背景层和细节层,然后在背景层的融合中运用分数阶边缘检测掩模保持边缘信息,在细节层中引入分数阶梯度能量算子进行权值分配.实验结果表明,与整数阶梯度能量清晰度算子相比,本文所提出的分数阶梯度能量算子符合人眼视觉感知且更加敏锐.上述融合方法有效避免了融合图像中的伪影和块状效应,更加充分地保留了源图像信息.

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 L 0 gradient minimization smoothing method,and then a fractionalorder 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.