Medical image fusion algorithm based on two-level multiscale decomposition and human visual characteristic

Aiming at the problem of insufficient classification of image information in the existing image fusion literature, which leads to insufficient image detail processing capabilities, this paper proposes a two-level multi-scale medical image fusion algorithm based on human visual characteristics. Four different methods, including the combination of regional visual contrast and PCNN, are used to fuse the images obtained by decomposing the source image in two levels of NSST and NSCT. A large number of experimental simulation results prove that compared with the existing mainstream image fusion algorithms; the image fusion algorithm proposed in this paper has greater advantages in terms of visual effects and objective indicators.