Dynamic Infrared and Visible Image Sequence Fusion Based on DT-CWT Using GGD

A novel fusion method is proposed for image sequence which based on the non-Gaussian statistical modeling of wavelet coefficients. Firstly, the source images are decomposed by dual tree complex wavelet transform (DT-CWT) respectively. Then, the wavelet coefficients are modeled using the generalized Gaussian distribution (GGD). Saliency measure, the weighted coefficient, is calculated by estimating distribution parameters. The pair of coefficients is fused through weighted average. Finally, the fused coefficients are reconstructed into a single fused image. The quality of the fused image is evaluated by three metric: entropy, mutual information and QAB/F.The experimental results demonstrate that performance of the proposed method is prior to other two fusion approaches for infrared and visible dynamic image sequence.