使用二维EMD的红外和彩色可见光图像融合

针对红外和彩色可见光图像的融合，提出了一种基于二维经验模式分解（BEMD）的新的融合方法。源图像由BEMD分解成为本征模式函数集（IMFs）和残余；再将红外图像的IMFs和残余分别与对应可见光图像的IMFs和残余进行灰度范围匹配后，用加权平均方法进行融合；最后由BEMD重构成融合图像。用此法所得的融合图像增强了红外图像的细节并具有与可见光图像相似的自然色彩。实验中将此法与传统的小波变换方法和主成分分析方法进行了比较，还与经验模式分解（EMD）和复经验模式分解（CEMD）的方法进行了比较，实验结果都证明了该方法的融合效果最优。

Novel fusion method of infrared and color visible images using BEMD

A novel color fusion method is proposed for the infrared and visible images using the Bidimentional Empirical Mode Decomposition（BEMD）.Firstly,the source images are decomposed into a set of Intrinsic Mode Functions（IMFs） and the residue by BEMD.Then,the range of pixel value of every IMF of the infrared image is adjusted to meet the range of the visible image.The fused IMFs and the residue are obtained by the weighted averaging and which are reconstructed into a single fused image by BEMD at last.Using this method,the fused image not only is enhanced in detail but also has color information similar to the source color visible image.In the experiment,compared with the DWT,PCA and EMD,CEMD,the results show that the proposed method is the best.