Genetic programming on GPUs for image processing
Department Of Computer Science, Memorial University, St John’s, Canada
International Journal of High Performance Systems Architecture, Volume 1, Number 4, 2008, p.231-240
@article{harding2008genetic,
title={Genetic programming on GPUs for image processing},
author={Harding, S. and Banzhaf, W.},
journal={International Journal of High Performance Systems Architecture},
volume={1},
number={4},
pages={231–240},
issn={1751-6528},
year={2008},
publisher={Inderscience}
}
The evolution of image filters using genetic programming is a relatively unexplored task. This is most likely due to the high computational cost of evaluating the evolved programs. The parallel processors available on modern graphics cards can be used to greatly increase the speed of evaluation. Previous papers in this area dealt with tasks such as noise reduction and edge detection. Here we demonstrate that other more complicated processes can also be successfully evolved and that we can ‘reverse engineer’ the output from filters used in common graphics manipulation programs.
January 23, 2011 by hgpu
