基于Contourlet变换和模糊理论的图像融合算法

摘要

For the fusion of visual and infrared images,a new method is proposed based on the contourlel transform and fuzzy theory. Firstly,the source images are decomposed using conlourlel transform. Secondly,the contourlet coefficients are fused with different rules. Fuzzy theory is used to fuse low frequency sub-band,which can adaptively calculate the wavelet coefficients weights of original images. While the high frequency sub-bands are merged with local energy as weight. Ultimately,the fusion image is obtained through an inversed contourlet transform. The experimental results show that the fusion scheme can get better visual effect and preserve image detail information of the original images. It is an effective and practical fusion method.%提出一种基于Contourlet变换和模糊理论的红外与可见光图像融合算法.首先,对源图像进行Contourlet变换；随后对低频和高频的小波系数采用不同的融合规则,即低频部分采用基于模糊集的自适应加权融合方法,高频部分采用基于区域小波能量加权的方法；最后再通过contourlet逆变换,获得融合图像.实验结果表明该算法能够较好地保留源图像的细节信息,具有较好的视觉效果,是一种有效实用的方法.