关键词: 图像融合, 脉冲耦合神经网络, 小波变换, 空间频率, 点火映射图

Abstract: For PCNN（Pulse Coupled Neural Network） has particular advantage in image processing，a novel fusion algorithm of multi-sensor image is proposed based on wavelet transform and PCNN.Original images are decomposed by wavelet transform，and the sub-band images at different scales are obtained.A fusion rule is given through making use of synchronous pulse bursts.This method uses SF（Spatial Frequency） of wavelet coefficients at different scales as the linking strength of the corresponding neuron.After the processing of PCNN with the adaptive strength，new fire mapping images in wavelet domain are obtained.According to the fire mapping images，the fusion coefficients are decided by the compare-select operator.The region consistency test is used on the fusion coefficients to obtain the final fusion coefficients.Fusion images are obtained by wavelet inverse transform.Experimental results illustrate that this algorithm is efficient to integrate important information from the original images and obtains fusion images，which outperforms wavelet，PCNN，and so on both in visual quality and objective evaluation index.

Key words: image fusion, pulse coupled neural network, wavelet transform, spatial frequency, fire mapping image