一种有效的形态小波多聚焦图像融合算法

An effective multi-focus image fusion algorithm based on morphological wavelets

多聚焦图像融合的关键问题是如何更好地保持源图像的轮廓信息和细节信息。形态小波具有小波变换的多层次分解特性和形态学的非线性特性。提出了一种基于形态小波变换的多聚焦图像融合算法。根据形态小波分解信号的特点,分别对高频系数和低频系数设计不同的融合规则:高频系数采用方向相关方法,最大程度保留细节和细节信息的方向特性;低频系数采用加权平均方法,该方法轮廓明显,最大程度地保留了轮廓信息。实验结果表明:该方法融合图像效果优于传统图像融合方法。

The key point of multi-focus image fusion is to keep the outline and detail information of the original image better. As morphological wavelet integrates the properties of multi-level decomposition owned by wavelet transform and the non-linear features possessed by morphology, this paper proposes a multi-focus image fu- sion algorithm based on morphological wavelet. According to the characteristics of wavelet signal decomposition, this paper designs different fusion rules for high-frequency coefficients and low-frequency coefficients respectively. High-frequency coefficients use the method of achieving direction-related to reserve the details and orientation. However, the low-frequency coefficients adopt the method of weighted average to remain the obvious outline information maximally. The results indicate that the proposed image fusion method has better effects than traditional image fusion method.