基于冗余小波变换与引导滤波的多聚焦图像融合

针对传统多尺度变换在多聚焦图像融合中存在的边缘晕圈问题,提出了一种基于冗余小波变换与引导滤波的多聚焦图像融合算法。首先,利用冗余小波变换对图像进行多尺度分解,将源图像分解为一个相似平面和一系列小波平面,该多尺度分解能够有效地提取源图像中的细节信息；然后,对相似平面和小波平面分别采用引导滤波的加权融合规则来构造加权映射,从而得到相似平面和小波平面的加权融合系数；最后,进行冗余小波逆变换,即可得到融合结果图。实验结果表明,与传统融合算法相比,所提算法能够更好地体现图像边缘的细节特征,取得了较好的融合效果。

Multi-focus Image Fusion Based on Redundant Wavelet Transform and Guided Filtering

For the problem of edge halo in multi-focus image fusion based on traditional multi-scale transform,this paper proposed a novel method of image fusion based on redundant wavelet transform and guided filtering.Firstly,the source images are decomposed by the redundant wavelet transform,and a similar plane and a series of wavelet planes are obtained.The multi-scale decomposition can effectively extract the detail information in the source images.Then the weighted fusion rules of guided filtering are respectively used in the similar plane and the wavelet planes,and the weighted maps are constructed to obtain the weighted fusion coefficients of the similar plane and the wavelet planes.Finally,the redundant wavelet inverse transform is used to obtain the fusion image.The experiment results show that the proposed method can better reflect edge detail features of the images and can achieve better fusion results compared with the traditional fusion methods.