基于NSST和NLMF的多聚焦图像融合

Multi-focus image fusion based on NSST and NLMF

为对融合图像的信息丰富度、边缘清晰度以及视觉效果作进一步的提升,设计了一种基于非下采样剪切波变换(NSST)结合非局部均值滤波(NLMF)的多聚焦图像融合算法。首先,将源图像通过NSST变换进行多尺度、多方向分解得到高、低频子带系数。其次,对低频子带系数采用局部区域的改进拉普拉斯能量和以及非局部均值滤波融合方法构建低频子带系数融合权重;对高频子带系数采用基于相关系数的空间频率与能量相结合的融合规则,再加以相位一致性规则,构建高频子带系数融合权重;最后,通过NSST反变换得到最终融合图像。从三组不同聚焦图像的实验结果来看,所提算法不论是在主观视觉上,还是在客观评价上,融合图像的轮廓、纹理等信息保留度以及视觉清晰度都有较好的提升。

In order to further improve the information richness,edge clarity and visual effect of the fused image,a multi-focus image fusion algorithm based on non-downsampling shear wave transform(NSST)combined with non-local mean filtering(NLMF)was designed.Firstly,the source image was multi-scale and multi-directionally decomposed by NSST transform to obtain high and low frequency subband coefficients.Secondly,the improved Sum Modified Laplacian and the non-local mean filter fusion method were used for the low-frequency subband coefficients to construct the fusion weights of low-frequency subband coefficient;For the high-frequency subband coefficients,fusion rules based on the combination of spatial frequency and energy based on correlation coefficients were used,and then phase consistency rules were added to construct the fusion weights of high-frequency subband coefficient;Finally,the final fusion image was obtained by inverse NSST transformation.The experimental results from three sets of different focused images show that:Whether the algorithm in this paper is in subjective vision or objective evaluation,the information retention and visual clarity of the fusion image′s contour and texture have been improved.