Experiments on Genetic Programming Based Image Artefact Detection

Abstract

One of the interesting image processing applications is to detect and/or restore a damaged image. Because image damage would vary in different ways, a straightforward method is to use a program to represent the damage. Then, the type of artefact can be searched by applying programs to the original image and comparing with the target image. The run-time environment of a program is the structure of the execution resources. In this paper, we define a cellular automaton based structure as the run-time environment and use genetic programming (GP) to find the proper program for the given image artefacts. The results show that an effective GP engine requires careful configuration. The important lesson learned from the experiments is also discussed.