一种新的多聚焦图像融合算法

New Multi-Focus Image Fusion Algorithm

提出了一种基于小波-Contourlet变换的多聚焦图像融合算法;该算法首先采用小波-Contourlet变换对源图像进行多尺度分解,得到高频和低频图像;接着根据高、低频分量各自的区域特性,采用不同的融合规则进行处理,得到小波-Contourlet变换域的融合系数,最后通过反变换得到融合图像;采用信息熵、标准差和互信息3个评价标准,将该算法和传统的小波算法和Contourlet算法的融合结果进行了比较;实验结果表明,该算法获得的评价指标都优于其它算法,且融合图像较好地从源图像中提取了有用信息,提高了融合质量。

A new multi--focus image fusion algorithm based on wavelet based contourlet is proposed. Firstly, multi--scale decomposition is performed on source images using wavelet based eontourlet transform to get high--frequency and low-frequency images. And then, according to the different region statistics between high--frequency and low--frequency, the fused coefficients in wavelet based contourlet domain are obtained by using different fusion rules. Finally, the inverse wavelet based contourlet transform is utilized to obtain fused image. The fused image by the proposed method is evaluated with some parameters such as entropy, standard deviation, mutual information, in comparison with the wavelet based and eontourlet based schemes. The experimental results show that the proposed method outperforms other conventional methods. At the same time, it can extract all useful information from the original images and improve fusion quality.