一种基于非下采样Contourlet变换多聚焦图像融合算法

针对现有小波类图像融合算法的不足,提出了一种基于非下采样Contourlet变换多聚焦图像融合算法,并在Contourlet域中引入了局部区域可见度以及局部方向能量的概念.针对低频子带系数和各带通方向子带系数分别提出了基于局部区域可见度以及基于局部方向能量的系数选择方案.通过对多聚焦图像融合的仿真实验,表明该算法相对于传统的基于离散小波变换和离散小波框架变换融合算法能够有效减少有用信息的丢失以及虚假信息的引入,同时能够从源图像中提取更多的有用信息并注入到融合图像中, 得到更好视觉效果和更优量化指标的融合图像.

Fusion of Multifocus Images Based on the Nonsubsampled Contourlet Transform

Focusing on the deficiencies of existing wavelet based algorithm, a novel algorithm for multifocus images fusion based on the nonsubsampled contourlet transform (NSCT) is proposed. And, the concepts of the local area visibility (LAVI) and the local oriented energy (LOE) are introduced in the contourlet domain. The selection principle of the low frequency subband coefficients based on the LAVI and the selection principle of the bandpass directional subband coefficients based on the LOE are presented respectively. The experimental results demonstrate that the proposed algorithm, compared to the methods based on the discrete wavelet transform and the discrete wavelet frame transform, can effectively reduce the loss of the useful information and the introduction of the artificial information. In addition, the proposed algorithm can extract more useful information from the source images, and make the fused image with higher performance in terms of both visual quality and objective evaluation criteria.