Evolution of Image Filters on Graphics Processor Units Using Cartesian Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4202

  author =       "Simon Harding",
  title =        "Evolution of Image Filters on Graphics Processor Units
                 Using Cartesian Genetic Programming",
  booktitle =    "2008 IEEE World Congress on Computational
  year =         "2008",
  editor =       "Jun Wang",
  pages =        "1921--1928",
  address =      "Hong Kong",
  month =        "1-6 " # jun,
  organization = "IEEE Computational Intelligence Society",
  publisher =    "IEEE Press",
  isbn13 =       "978-1-4244-1823-7",
  file =         "EC0465.pdf",
  DOI =          "doi:10.1109/CEC.2008.4631051",
  abstract =     "Graphics processor units are fast, inexpensive
                 parallel computing devices. Recently there has been
                 great interest in harnessing this power for various
                 types of scientific computation, including genetic
                 programming. In previous work, we have shown that using
                 the graphics processor provides dramatic speed
                 improvements over a standard CPU in the context of
                 fitness evaluation. In this work, we use Cartesian
                 Genetic Programming to generate shader programs that
                 implement image filter operations. Using the GPU, we
                 can rapidly apply these programs to each pixel in an
                 image and evaluate the performance of a given filter.
                 We show that we can successfully evolve noise removal
                 filters that produce better image quality than a
                 standard median filter.",
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 Genetic Programming, GPU",
  notes =        "WCCI 2008 - A joint meeting of the IEEE, the INNS, the
                 EPS and the IET.",

Genetic Programming entries for Simon Harding