| Abstract | Evolutive 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. We have proposed a GP-based image predictor that is specifically evolved for each input image. It is a radical departure from conventional "fixed algorithm", "man-made algorithm" and "hand-made program" towards new paradigm such as "content-specific algorithm", "machine-generated algorithm/program". In this course, the predictor generation algorithm, its basic performance, application examples and some speeding up techniques of the evolution process will be presented. |