Approximate Circuits in Low-Power Image and Video Processing: The Approximate Median Filter

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Lukas Sekanina and Zdenek Vasicek and Vojtech Mrazek",
  title =        "Approximate Circuits in Low-Power Image and Video
                 Processing: The Approximate Median Filter",
  journal =      "Radioengineering",
  year =         "2017",
  volume =       "26",
  number =       "3",
  pages =        "623--632",
  month =        sep,
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 genetic programming, Approximate computing, circuit
                 design, evolutionary computation, image filter",
  ISSN =         "1805-9600",
  URL =          "",
  URL =          "",
  DOI =          "doi:10.13164/re.2017.0623",
  size =         "10 pages",
  abstract =     "Low power image and video processing circuits are
                 crucial in many applications of computer vision.
                 Traditional techniques used to reduce power consumption
                 in these applications have recently been accompanied by
                 circuit approximation methods which exploit the fact
                 that these applications are highly error resilient and,
                 hence, the quality of image processing can be traded
                 for power consumption. On the basis of a literature
                 survey, we identified the components whose
                 implementations are the most frequently approximated
                 and the methods used for obtaining these
                 approximations. One of the components is the median
                 image filter. We propose, evaluate and compare two
                 approximation strategies based on Cartesian genetic
                 programming applied to approximate various common
                 implementations of the median filter. For filters
                 developed using these approximation strategies,
                 trade-offs between the quality of filtering and power
                 consumption are investigated. Under conditions of our
                 experiments we conclude that better tradeoffs are
                 achieved when the image filter is evolved from scratch
                 rather than a conventional filter is approximated.",

Genetic Programming entries for Lukas Sekanina Zdenek Vasicek Vojtech Mrazek