Accelerating pixel predictor evolution using edge-based class separation | IEEE Conference Publication | IEEE Xplore

Accelerating pixel predictor evolution using edge-based class separation


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 ...Show More

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.
Date of Conference: 08-10 December 2010
Date Added to IEEE Xplore: 28 January 2011
ISBN Information:
Conference Location: Nagoya, Japan

References

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