A Gray Image Enhancing Algorithm Based on g-l-PSO

Regular Beta function gives a uniform expression of gray image contrast transform functions.But the two parameters of Beta function relate to specific images and they are difficult to find reasonable parameter values.This paper analyzed the traditional PSO algorithm and proposed a g-l-PSO algorithm.Using the local optimal solution for the population genetic and the variation was based on the global optimal solution.The Beta function parameters were determined g-l-PSO through the fitness assessment.This work can obtain the most suitable parameter values for current image.Three typical images enhancing experiments show that this approach is feasible.