This paper describes a method for automatically approximating an unknown image transformation from an original image to its target image by the use of a sequence of several known image filters, where the target image is an ideally processed image made manually. This automatic construction problem is regarded as a combinatorial optimization problem for the ordering of image filters and a genetic algorithm is employed to solve it. A population of individuals whose chromosomes represent sequences of image filters is evolved. In generation iterations, each individual is evaluated based on the difference between the target image and the image processed according to the filter sequence defined by its chromosome. This method can deal with arbitrary image transformations, and it can be applied to expert systems for image processing.
