Fusion of Infrared and Visible Light Images Based on Compressive Sensing

Through NSCT transformation, an image will be decomposed into a low-pass sub-band and K-direction sub-bands, but the sparsity is different for each direction. Therefore, this paper proposes a new way for fusion of infrared and visible light images, which is based on improved compressive sensing. First, strengthen the infrared image. Then, making a NSCT decomposition to the enhanced infrared image and visible light image, next doing compression to high frequency sub-bands by improved compressive sensing, and after that to fuse them. For the low-pass sub-band, it uses block DCT of high frequency energy rule to fuse them. Finally, it gets fusion image by reconstruction of compressive sensing and inverse NSCT transform for data which has been fused. When compared with the traditional compressive Sensing method, the simulation shows that it not only improves parameters, such as entropy, and standard deviation, average gradient, but reduces the amount of data and running time effectively.