摘要
提出了一种基于静态小波变换(SWT)和2代曲波(curvelet)变换的图像融合算法.首先将原图像分别进行SWT变换得到高、低频分量.然后,对低频分量采用基于2代曲波变换的方法进行融合,对高频分量基于绝对值最大的方法进行融合.最后进行SWT逆变换得到最终的融合图像.实验结果表明,该算法具有SWT变换和2代曲波变换二者的优点,主客观评价均优于单独SWT变换和单独2代曲波变换融合算法,也优于离散小波变换(DWT)和曲波变换相结合的融合算法.
An image fusion algorithm based on stationary wavelet transform(SWT) and second generation curvelet transform is proposed.High and low frequency components of the original images are respectively gotten by using SWT transform firstly.Then the low frequency components are fused by the image fusion method based on the second generation curvelet transform,and high frequency components are fused by the method based on the maximum absolute values.Finally,the inverse SWT transform is applied to getting the fused image.Experimental results show that the algorithm has the advantages of both the second generation curvelet transform and SWT transform.The subjective and the objective evaluations of the proposed algorithm are superior to individual second generation curvelet transform and individual SWT transform fusion algorithm alone,and also better than the fusion algorithm by combining discrete wavelet transform(DWT) and curvelet transform.
出处
《信息与控制》
CSCD
北大核心
2012年第3期278-282,共5页
Information and Control
关键词
图像融合
静态小波变换
曲波变换
评价指标
多聚焦图像
image fusion
stationary wavelet transform
curvelet transform
evaluation index
multifocus image