基于多分辨率的非参数正交多项式医学图像融合方法

A Multi-Resolution Medical Image Fusion Method Based on Nonparametric Orthogonal Polynomials

基于估计理论的图像融合方法都是假设图像偏移或噪声服从高斯混合分布,容易造成模型不匹配和丢失局部细节等问题.文中提出一种基于小波的多分辨率的非参数正交多项式医学图像融合方法.首先,对图像进行多分辨率分解.对低频部分,根据图像信息模型和非参数正交多项式混合模型,采用非参数期望最大法估计模型参数,获得低频融合结果.对高频部分,采用系数绝对值选大法进行融合.然后,将高频和低频部分结果进行反变换,得到最终融合图像.实验结果表明,该方法融合质量优于其它方法,融合时间大为缩短.

Image fusion algorithms based on estimation theory assume that all distortions should follow Gaussian distribution, which causes model mismatch, local details losing and time-consuming. A medical image fusion algorithm is presented based on multi-resolution and nonparametric orthogonal polynomials. Firstly, the source images are decomposed into multi-resolution representations. Then, the NEM algorithm is used to estimate the parameters of the image information model and the non-parametric orthogonal polynomials image mixture model. Thus, the fusion result of low frequency band image is got. For the high frequency band image, the maximum absolute value of the coefficient is applied. Finally, the fused image is obtained by taking the inverse transformation of the composed coefficients. The experimental results show that the proposed algorithm achieves better performance than other fusion methods and the fusion time is considerably reduced.