A study on an evolutionary pixel predictor and its properties

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

  author =       "Seishi Takamura and Masaaki Matsumura and 
                 Yoshiyuki Yashima",
  title =        "A study on an evolutionary pixel predictor and its
  booktitle =    "16th IEEE International Conference on Image Processing
                 (ICIP), 2009",
  year =         "2009",
  month =        nov,
  pages =        "1921--1924",
  keywords =     "genetic algorithms, genetic programming, lossless
                 image coding, prediction methods",
  abstract =     "Evolutionary methods based on genetic programming (GP)
                 enable dynamic algorithm generation, and have been
                 successfully applied to many areas such as plant
                 control, robot control, and stock market prediction.
                 However, conventional image/video coding methods such
                 as JPEG and H.264 all use fixed (non-dynamic)
                 algorithms without exception. In this article, we
                 introduce a GP-based image predictor that is
                 specifically evolved for each input image. Experimental
                 results demonstrate 2.9percent less entropy (overhead
                 included) than CALIC's gradient adjusted predictor.",
  DOI =          "doi:10.1109/ICIP.2009.5413714",
  ISSN =         "1522-4880",
  notes =        "Also known as \cite{5413714}",

Genetic Programming entries for Seishi Takamura Masaaki Matsumura Yoshiyuki Yashima