针对多聚焦图像融合中聚焦物体边缘衔接处产生伪影的问题，提出一种基于非下采样Contourlet变换(NSCT)与引导滤波的多聚焦图像融合算法。该算法对多聚焦图像进行NSCT分解后，利用基于边缘的加权融合方案处理低频子带系数，利用双向拉普拉斯滤波器提取带通方向子带系数的边缘和显著信息，通过引导滤波器对初始融合权重进行修正，最后利用NSCT重构获得融合后的多聚焦图像。实验结果表明，与其他融合算法相比，本文算法提高了融合图像的信息丰富度和清晰度，避免在聚焦物体边缘衔接处产生伪影，提高了融合图像的总体质量。

Aiming at the problem of artifacts in the convergence of object edges in multi-focus images fusion, a multi-focus images fusion algorithm is proposed based on non-subsampled Contourlet transform(NSCT) and guided filtering, by which the multi-focus images are decomposed. For the sub-band coefficients of low-frequency, an edge-based weighted fusion scheme is adopted, while, for sub-band coefficients of band-pass directional, bidirectional Laplacian filtering is utilized to extract edge and significant information. Meanwhile, the guided filter is used to correct initial fusion weigh, and NSCT reconstruction is performed to obtain fused multi-focus image. The experimental results show that, compared with seven other fusion algorithms, the proposed algorithm can improve richness and clarity of fusion image, avoid artifacts at objects edge, and improve the fused image′s general quality.