基于Contourlet变换的彩色图像融合算法

Color Image Fusion Algorithm Using the Contourlet Transform

以红外和彩色可见光图像为研究对象,提出一种基于Contourlet变换的彩色图像融合算法.算法首先通过IHS(Intensity-Hue-Saturation)变换将彩色可见光图像从RGB颜色空间变换到IHS空间,进而利用Contourlet变换和加权融合规则将I分量图像与红外图像进行融合,然后将得到的灰度融合图像进行线性拉伸以获得与I分量相同的均值和方差,最后用拉伸后的灰度融合图像替换原来的I分量,并通过IHS逆变换得到最终的RGB彩色融合图像.算法一方面将Contourlet变换这一新的数学工具引入到图像融合中,另一方面提供了一种新的红外和可见光图像的彩色融合方法.实验结果表明,同样采用本文的彩色融合方法,Contourlet变换的融合结果优于小波变换,而且本文彩色融合方法的融合性能明显超过传统IHS变换融合法.

With the particular research on thermal and visual images, a color image fusion algorithm using the contourlet transform is presented.Firstly, through the IHS （Intensity-Hue-Saturation） transform, the color visual image is converted from RGB color space to IHS space. Next, with the contourlet transform and weighted average fusion rule, the intensity component and thermal image are merged into a grayscale image, which is then linearly stretched to have the same mean and variance as the intensity component. Finally,the stretched grayscale fused image replaces the original intensity component,and the final RGB color fused image is achieved by the inverse IHS transform with the H, S and replacement component. On the one hand, with the proposed scheme, the contourlet transform as a new mathematical tool is introduced to image fusion area. On the other hand, the algorithm provided a new color image fusion strategy of thermal and visual images. The experimental results show that, with the proposed color fusion method,the fused image produced by the contourlet transform is of better quality than that obtained through the wavelet transform. Moreover, the color fusion approach obviously improves fusion performance over the traditional IHS transform fusion method.