Spiking cortical model for multifocus image fusion

Spiking Cortical Model (SCM) is derived from primate visual cortex. It has a high sensitivity for low intensities of stimulus, but low sensitivity for high intensities, and is suitable for image processing. This paper adopts an improved SCM for multifocus image fusion. Firstly we analyze and compare various image clarity measures, and then we propose a new SCM fusion method based on a composite image clarity criterion which synthesizes virtues of two classic clarity criteria. As to the iteration number of SCM model for image processing, we introduce time matrix as an adaptive setting method instead of using fixed constant, which can automatically and adaptively calculate iteration number for each image accurately. Besides, we optimize pulsing output matrix of source image according to natural optical focus principle before forming and outputting the final fused image. In order to verify the effectiveness of the proposed method, we compare it with other ten methods under four fusion effect evaluation indices. The experimental results show that the proposed approach can obtain better fusion results than others, and is an effective multifocus image fusion method.