关键词: 小波核, 支持度变换, 脉冲耦合神经网络, 绝对值最大选取融合规则

Abstract: To extract the salient features of the image more effectively and improve the performance of multi-focus image fusion，a new method of image fusion is proposed in this paper.For the defect of image feature can’t be extracted by filter generated through the use of Gaussian kernel basis.In this paper，exploiting the advantages of approximate orthogonal of wavelet kernel and signal local analysis for support value transform，Pulse-Coupled Neural Network is applied for the low frequency information，while the maximum absolute value selection fusion rule for the high frequency information.The experiment data and theory analysis show that this method effectively improves the salient features of the image.The information entropy evaluation results etc，are raised and visual effects is improved than the method using support value transform with Gaussian kernel.

Key words: wavelet kernel, support value transform, Pulse-Coupled Neural Network（PCNN）, the maximum absolute value selection fusion rule