An Effective Image Fusion Method Based on Nonsubsampled Contourlet Transform and Pulse Coupled Neural Network
In order to solve the problem of spectral distortion and the fuzzy texture in visible and infrared image fusion technology,a novel visible and infrared image fusion method based on the Nousubsampled Contourlet Transform (NSCT) and Pulse Coupled Neural Networks (PCNN) is proposed in this paper.First,we gain three components of visible image,luminance Ⅰ,chrominance H and saturation S,using the IHS transform.Then,we gain three coefficients,low frequency subband,passband sub-band and high frequency coefficient by decomposing the component Ⅰ and infrared image with the help of the NSCT.Next,we use weighted-sum method to fuse the low frequency sub-band and PCNN method to fuse the other sub-band coefficient respectively.At last,we gain the fusion image by using the inverse IHS transform on the fusion component Ⅰ gained by the inverse NSCT transform.Experiments show that our method have better fusion quality and can be more better to keep the visible spectral and detail information than some traditional methods such as,Laplace method,Wavelet method and Lifting Wavelet method.
IHS transform Nonsubsampled Contourlet transform Pulse Coupled Neural Networks transform image fusion
Lijuan Ma Chunhui Zhao
College of Information and Communication Engineering University of Harbin EngineeringHarbin, Heilongjiang Province, China
国际会议
太原
英文
8-12
2012-12-08（万方平台首次上网日期，不代表论文的发表时间）