@InProceedings{Kybic-ICIP2004,
  IS = { zkontrolovano 13 Jan 2005 },
  UPDATE  = { 2004-11-27 },
  author =       {Jan Kybic},
  title =        {High-Dimensional Mutual Information Estimation 
                  for Image Registration},
  booktitle =    {{ICIP'04}: Proceedings of the 2004 {IEEE}
                  International Conference on Image Processing },
  publisher =    {IEEE Computer Society},
  address =      {445 Hoes Lane, Piscataway, U.S.A. },
  venue =        {Singapore},
  isbn =         {0-7803-8555-1},
  pages =        {4},
  project =      {LN00B096},
  annote = { We present a~new algorithm for mutual information
    estimation for image registration based on the nearest neighbor
    entropy estimator of Kozachenko and Leonenko. We modify the
    algorithm to be numerically robust and computationally efficient,
    with optimal asymptotic complexity O(N_pixels d_dim).  We propose two MI-based
    criteria exploiting the high-dimensionality of the feature space
    and show their effectiveness in determining the correct alignment
    even in difficult cases when classical criteria fail.},
  keywords = { image registration, mutual information, high-dimensional, entropy, 
    Kozachenko-Leonenko, nearest neighbor},
  year =         {2004},
  day =          {24--27},
  month =        {October},
  psurl =        { [Pdf,334KB]},
  url =          {ftp://cmp.felk.cvut.cz/pub/cmp/articles/kybic/Kybic-ICIP2004.pdf},
}