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Empirical mode decomposition (EMD) is good at analyzing nonstationary and nonlinear signals while support vector machines (SVMs) are widely used for classification. In this paper, a combination of EMD and SVM is proposed as an improved method for fusing multifocus images. Experimental results show that the proposed method is superior to the fusion methods based on à-trous wavelet transform (AWT) and EMD in terms of quantitative analyses by Root Mean Squared Error (RMSE) and Mutual Information (MI).