Accelerating pixel predictor evolution using edge-based class separation

Created by W.Langdon from gp-bibliography.bib Revision:1.8081

@InProceedings{Takamura:2010:PCS,

• author = "Seishi Takamura and Masaaki Matsumura and Hirohisa Jozawa",
• title = "Accelerating pixel predictor evolution using edge-based class separation",
• booktitle = "Picture Coding Symposium (PCS 2010)",
• year = "2010",
• month = "8-10 " # dec,
• pages = "106--109",
• 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, one of the challenges of this approach is its high computational complexity. Conventional image/video coding methods such as JPEG and H.264 all use fixed (non-dynamic) algorithms without exception. However, one of the challenges of this approach is its high computational complexity. In this article, we introduce a GP-based image predictor that is specifically evolved for each input image, as well as local image properties such as edge direction. Via the simulation, proposed method demonstrated ~180 times faster evolution speed and 0.02-0.1 bit/pel lower bit rate than previous method.",
• keywords = "genetic algorithms, genetic programming, computational complexity, dynamic algorithm generation, edge-based class separation, evolutionary method, image coding, image predictor, pixel predictor evolution, video coding, image coding",
• DOI = "doi:10.1109/PCS.2010.5702434",
• notes = "NTT Cyber Space Laboratories, NTT Corporation. Also known as \cite{5702434}",

}

Genetic Programming entries for Seishi Takamura Masaaki Matsumura Hirohisa Jozawa

Citations