Research on Fusion of Infrared and Visible Images Based on Directionlet Transform

Directionlet transform is a lattice-based skewed discrete wavelet transform. It has advantages of multi-directional and anisotropy compared with standard two-dimensional wavelet transform, thus, it is better at describing the characteristics of images. For the research focus of different-source image fusion, a novel fusion algorithm based on Directionlet transform was proposed, and the fusion speed was improved efficiently by combing the transform with a lifting scheme. Firstly, between transform direction and alignment direction, two registered source images were decomposed by using lifting Directionlet transform respectively in different times, thus anisotropic sub images were obtained. Then, the low frequency components were combined averagely and the selection principle of high frequency sub images were based on which has stronger anisotropic edge information. Finally, the fused image was obtained by using inverse Directionlet transform. Experimental results show that the fusion effect and speed are both better than standard wavelet transform and other second generation wavelet transform.