Infrared Image And Visible Light Image Fusion Based On Nonsubsampled Contourlet Transform And The Gradient Of Uniformity

The nonsubsampled contourlet transform (NSCT) is a new multi-resolution transform, which can give an asymptotic representation of edges and contours in image by virtue of its characteristics of multi-direction, flexible multi-scale and shift-invariant simultaneity. For fusion between visible light image and infrared image, this paper proposed a new method based on nonsubsampled contourlet transform and the visual characteristics of region. Firstly, two original images were decomposed into different frequency sub-band coefficients by using NSCT, and then the selection of the low frequency subband coefficient and the bandpass direction subband coefficient was discussed respectively. For the choice of low frequency subband coefficient, this paper proposed a new method that chose coefficient based on the visual characteristics of region and gradient characteristics. For the choice of bandpass direction subband coefficient, this paper uses a direct method that chose the coefficient based on maximum regional uniformity obtained by the visual characteristics of region. Finally, the fused image was obtained by performing the inverse NSCT on the combined coefficients. The experimental results show that this fusion algorithm proposed in this paper achieved significant results to extract target in the infrared image and preserve edge of the target. At the same time, it also achieved good results to effectively preserve image details in the visible light image.