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中文摘要：
以多聚焦图像为研究对象，提出一种新的基于二次融合多特征的融合方法。利用模糊C-均值聚类算法（FCM）在多特征形成的特征空间上对图像区域分割，并在此基础上执行多尺度小波分解。然后，获取源图像区域特征矩阵，经过二维主成分分析（2DPCA）变换后进行特征融合，根据融合后的特征计算区域中每个窗体的特征隶属度。引入模糊指标判断区域中窗体的模糊性，应用模糊熵和窗体能量获得加权因子．从而得到融合图像的小波系数，利用小波逆变换得到融合图像。
英文摘要：
Aimed at the multi-focus images, this paper proposes a new method for image fusion, i. e. , multi-focus image fusion based on second fusion and multi-feature. Firstly, the fuzzy C-means clustering algorithm （FCM） is used to segment image in feature space formed by multiple features of training samples, and then a multi-scale wavelet decomposition is performed on each region. Then, the feature matrix of source images region is obtained and the feature matrix is fused after two-dimensional principal component analysis （2DPCA） transform. The feature membership degree of each window is calculated according to the fusion fea- ture. The fuzzy degree of the image window can be estimated by the fuzziness index. The weighting factors are constructed based on the window energy and the fuzzy entropy. The wavelet coefficients of the fused image are acquired by weighting factors. Finally, the fused image is obtained by taking inverse wavelet transform. The performance of the image fusion method is evaluated by six criteria, including mean, variance, entropy, mutual information, spatial frequencies, and average gradient. The evaluation results indicate that the proposed image fusion method is effective.
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