Cauchy Biogeography-Based Optimization based on lateral inhibition for image matching

In this paper, a hybrid method of Cauchy Biogeography-Based Optimization (CBBO) and Lateral Inhibition (LI) is proposed to complete the task of complicated image matching. Lateral inhibition mechanism is adopted for image pre-process to make the intensity gradient in the image contrastively strengthened. Biogeography-Based Optimization (BBO) is a bio-inspired algorithm for global optimization which is based on the science of biogeography, searching for the global optimum mainly through two steps: migration and mutation. To promote the optimization performance, an improved version of the BBO method using Cauchy mutation operator is proposed. Cauchy mutation operator enhances the exploration ability of the algorithm and improves the diversity of population. The proposed LI-CBBO method for image matching inherits both the advantages of CBBO and lateral inhibition mechanism. Series of comparative experiments using Particle Swarm Optimization (PSO), LI-PSO, BBO and LI-BBO have been conducted to demonstrate the feasibility and effectiveness of the proposed LI-CBBO.