  Evolutionary algorithms are metaheuristic techniques that derive inspiration
from the natural process of evolution. They can efficiently solve (generate
acceptable quality of solution in reasonable time) complex optimization
(NP-Hard) problems. In this paper, automatic image enhancement is considered as
an optimization problem and three evolutionary algorithms (Genetic Algorithm,
Differential Evolution and Self Organizing Migration Algorithm) are employed to
search for an optimum solution. They are used to find an optimum parameter set
for an image enhancement transfer function. The aim is to maximize a fitness
criterion which is a measure of image contrast and the visibility of details in
the enhanced image. The enhancement results obtained using all three
evolutionary algorithms are compared amongst themselves and also with the
output of histogram equalization method.
