基于区域方向的NSCT与PCNN图像融合算法  

An Image Fusion Algorithm Based on NSCT and PCNN

作　　者：胡玉成[1] 王创新[1] 

机构地区：[1]长沙理工大学电气与信息工程学院,湖南长沙410000

出　　处：《电子科技》2014年第4期30-33,共4页Electronic Science and Technology

基　　金：湖南省教育厅基金资助项目(12C078)

摘　　要：针对NSCT移不变形、多尺度性和多方向性等特点,结合脉冲耦合神经网络,量融合规则,高频系数则采用PCNN融合规则。最终对融合后的系数经NSCT逆变换得到了融合图像。实验结果表明,该方法更好地保留了原图像中的有用信息,并提高了融合图像质量。An image fusion algorithm is proposed based on the shift-invariant, multi-scale and multi-directional NSCT and the pulse coupled neural network PCNN. First, a multiscale decomposition of the source image is per- formed with NSCT, and then with low coefficient using improved regional energy integration rules and the high fre- quency coefficients using PCNN fusion rule, the final fused image is obtained through NSCT inverse transform of the fused coefficients. Experimental results show that this method better retains useful information in the original image, and improves the quality of the fused image.

关 键 词：图像融合 非下采样轮廓波变换 脉冲耦合神经网络 区域能量 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]