基于分数阶小波与引导滤波的多聚焦图像融合方法

Multi-focus image fusion method based on fractional wavelet combined with guided filtering

针对多聚焦图像融合中存在易丢失细节信息、图像边缘处产生伪影等问题,提出了一种基于离散分数阶小波变换(DFRWT)结合引导滤波的多聚焦图像融合新方法。首先,采用DFRWT将多聚焦源图像进行多尺度分解,得到低频部分与高频部分。其次,为了使图像信息有效地融合,根据小波模系数的能量在不同阶数下的分布特征,选取最适合分数阶阶数,在低频部分应用拉普拉斯能量并获得初始决策,再用引导滤波修正决策图得到融合规则;高频部分采用分数阶空间频率的融合规则。最后,通过DFRWT逆变换获得融合后的图像。新方法与现有5种算法进行视觉对比和定量评估,仿真实验表明,本文方法有效抑制了Gibbs效应和边缘处的伪影效应,视觉效果和客观评价均令人满意,融合图像的质量优于已有的几类经典算法。

To address the problems of losing details and producing artifacts at image edges in multi-focus image fusion,a new multi-focus image fusion method was proposed based on discrete fractional wavelet transform(DFRWT) combined with guided filtering. First, DFRWT was utilized to decompose the source images at multiple scales,obtaining the low frequency part and high frequency part. Then, in light of the energy distribution traits of wavelet modulus coefficients at different orders, the most suitable fractional order was selected. In the low frequency part, the initial decision was obtained by applying the Laplacian energy sum, and then the fusion rule was yielded by modifying the decision graph with guided filtering. For the high frequency part, the fractional spatial frequency fusion rule was adopted. Such rules, which can improve the efficiency of the image information on fusion. Lastly, the inverse DFRWT processing was carried out to obtain the composite image. The new method was compared with the existing five algorithms for visual comparison experiments and quantitative evaluation. The simulation experiments show that the proposed method could effectively suppress Gibbs effects and edge artifacts effects. The validity and advantages of the proposed method were verified in terms of the visual effect and objective evaluation, outperforming several classical algorithms in the quality of image fusion.