A study on an evolutionary pixel predictor and its properties

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@InProceedings{TAKAMURA:2009:ICIP,

• author = "Seishi Takamura and Masaaki Matsumura and Yoshiyuki Yashima",
• title = "A study on an evolutionary pixel predictor and its properties",
• 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

Citations