The invention discloses an
image enhancement method based on an adaptive
immunity genetic algorithm. The
image enhancement method based on the adaptive
immunity genetic algorithm includes steps that S1, normalizing an image pixel
gray level f(x, y) to obtain n(x, y); S2, coding parameters (alpha, beta) to be optimized, randomly generating a group of initial individuals to form an initial
population, and inputting a control parameter
crossover probability p<c>, a
mutation probability p<m>, a
population size N, a maximum running algebra G and the like; S3, judging whether an
evolution algebra t is equal to G, if so, ending the
algorithm, and outputting the optimal solution of (alpha, beta), otherwise, turning to the next step; S4, using a roulette strategy to select M individuals, and carrying out
crossover and
mutation operations on the individuals according to
crossover and
mutation methods in genetic operation; S5, selecting two vaccines, the individuals to be vaccinated and a
vaccination point number to perform immunization, making a immunization choice after the
vaccination, and using the optimal individual retention strategy for the vaccinated
population; S6, obtaining the corresponding
nonlinear transformation function F(u) of each group of (alpha, beta), and using the
nonlinear transformation function to perform an image
gray level transformation to obtain an output image g(x, y).