基于MMPN和可调节链接强度的图像融合  

Image Fusion Based on MMPN and Adjustable Linking Strength

作　　者：王志慧[1,2] 赵保军[2] 沈庭芝[2] 

机构地区：[1]内蒙古大学电子信息工程学院电子工程系,内蒙古呼和浩特010021 [2]北京理工大学信息科学技术学院电子工程系,北京100081

出　　处：《电子学报》2010年第5期1162-1166,共5页Acta Electronica Sinica

基　　金：国家863基金项目(No.2007AA801106);内蒙古自然科学基金(No.2009BS0903);内蒙古自治区高等学校科学研究项目(No.NJ09005);内蒙古大学高层次引进人才科研启动基金(No.208045)

摘　　要：多小波系统可以同时具备正交性、紧支撑、对称性等特性,PCNN是具备生物视觉背景的第三代神经网络,用于图像处理有先天的优势.本文综合利用多小波和PCNN的优点,提出了基于PCNN脉冲数匹配度MMPN的图像融合算法.该算法中,各个神经元的链接强度依符合人类视觉特性的多小波域图像对比度而自适应地取值.实验表明,该算法可以更有效地提高融合图像的熵、标准差和质量测度,性能良好.A multi-wavelet system can simultaneously provide several features, such as orthogonality, finite support, symmetry and so on. PCNN that possesses biology vision background is the third generation neural network, so it has innate superiority used for image processing. Comprehensively utilizing the advantages of multi-wavelet and PCNN, this paper presents a image fusion algorithm based on match measure of pulse number-MMPN. In this algorithm, the linking strength of each nerve cell adaptively confirms value according to image contrast defined in multi-wavelet domain that is consistent with human visual characteristics. The experimental results show that the algorithm can effectively improve the entropy, standard deviation, and quality measure of the fused image,and has good performance.

关 键 词：脉冲耦合神经网络 脉冲数匹配度 链接强度 对比度 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]