IEEE Trans Biomed Eng. 2014 Jan;61(1):197-206. doi: 10.1109/TBME.2013.2279301. Epub 2013 Aug 21.
Traditional two-dimensional (2-D) fusion framework usually suffers from the loss of the between-slice information of the third dimension. For example, the fusion of three-dimensional (3-D) MRI slices must account for the information not only within the given slice but also the adjacent slices. In this paper, a fusion method is developed in 3-D shearlet space to overcome the drawback. On the other hand, the popularly used average-maximum fusion rule can capture only the local information but not any of the global information for it is implemented in a local window region. Thus, a global-to-local fusion rule is proposed. We firstly show the 3-D shearlet coefficients of the high-pass subbands are highly non-Gaussian. Then, we show this heavy-tailed phenomenon can be modeled by the generalized Gaussian density (GGD) and the global information between two subbands can be described by the Kullback-Leibler distance (KLD) of two GGDs. The finally fused global information can be selected according to the asymmetry of the KLD. Experiments on synthetic data and real data demonstrate that better fusion results can be obtained by the proposed method.
传统的二维（2-D）融合框架通常会丢失第三维的层间信息。例如，三维（3-D）磁共振成像（MRI）切片的融合不仅必须考虑给定切片内的信息，还必须考虑相邻切片的信息。在本文中，开发了一种在三维剪切波空间中的融合方法来克服这一缺点。另一方面，常用的平均-最大值融合规则只能捕获局部信息，而不能捕获任何全局信息，因为它是在局部窗口区域中实现的。因此，提出了一种从全局到局部的融合规则。我们首先表明高通子带的三维剪切波系数是高度非高斯的。然后，我们表明这种重尾现象可以用广义高斯密度（GGD）建模，并且两个子带之间的全局信息可以用两个GGD的库尔贝克-莱布勒散度（KLD）来描述。最终融合的全局信息可以根据KLD的不对称性来选择。对合成数据和真实数据的实验表明，所提出的方法可以获得更好的融合结果。
