FUSION OF INFRARED AND VISIBLE LIGHT IMAGES BASED ON NONSUBSAMPLED CONTOURLET TRANSFORM
一种基于非采样Contourlet变换红外图像与可见光图像融合算法

Focusing on the fusion problem of infrared and visible light images with the same scene,a novel multi-sensor image fusion algorithm based on the nonsubsampled contourlet transform(NSCT)was proposed.Firstly,the NSCT was performed on the source images at different scales and directions,thus the low frequency subband coefficients and varieties of directional bandpass subband coefficients were obtained.Secondly,for the low frequency subband coefficients,a 'weighted averaging' scheme based on the physical features of infrared images and visible light images was presented;while for the bandpass directional subband coefficients,a selection principle based on the local energy matching was developed,which was also consistent with the characteristics of the human vision system.Finally,the fused image was obtained by performing the inverse NSCT on the combined coefficients.Quantitative and qualitative analysis of the experimental results demonstrate that the proposed approach performs significantly better than the traditional methods based on the discrete wavelet transform and the discrete wavelet frame transform.