Infrared and Visible Image Fusion Based on Shearlet Transform and Image Enhancement

In order to fuse the visible and infrared images captured in low visibility conditions, a method based on shearlet transform(ST) and image enhancement is proposed in this paper. Shearlets are equipped with a simple mathematical structure similar to wavelets, which are associated to a multi-scale analysis. An image could be decomposed by ST in any scale and any direction, in which shearlets show a greater ability to fully capture the intrinsic geometrical features of multidimensional phenomena. Firstly, the infrared and visible images are decomposed by ST respectively; meanwhile all the sub-images of R, G and B channels of visible image are enhanced. Secondly, the statistical character of the directional coefficients decomposed by ST meet the generalized Gaussian distribution (GGD). So, the coefficients are estimated using absolute moment estimation in local neighbor in directional coefficients. The estimated scale parameter is used to measure the saliency and compute the weight. The fused coefficients are obtained by the weighted average and are reconstructed the final fused image. The results of experiment show that the fused image has the maximum value of entropy and is more accord with the human visual system.