Fusion of visible and infrared images based on spiking cortical model in nonsubsampled contourlet transform domain

Abstract

A novel fusion algorithm for spatially registered infrared and visible images fusion based on the spiking cortical model (SCM) in nonsubsampled contourlet transform (NSCT) domain is proposed in this paper. NSCT can effectively surmount the defect of the absence of shift-invariance in contourlet transform to avoid pseudo-Gibbs phenomena. Source images are decomposed by NSCT to acquire the coefficients of lowpass subbands and highpass subbands. In the proposed fusion method, the energy of Laplacian that computed by the lowpass subband, which stands for the edge features of the lowpass subband, is employed and inputted to motivate SCM. For the highpass subbands, a modified spatial frequency that calculated through the highpass subband is introduced and applied as the gradient features of the highpass subbands to motivate SCM. Experiments demonstrate the proposed algorithm can make great progress in image fusion, and achieve better effect than conventional methods in both objective evaluation and visual appearance.