EGGDD: An explicit dependency model for multi-modal medical image fusion in shift-invariant shearlet transform domain

@article{Wang2014EGGDDAE,
  title={EGGDD: An explicit dependency model for multi-modal medical image fusion in shift-invariant shearlet transform domain},
  author={Lei Wang and Bin Li and Lianfang Tian},
  journal={Information Fusion},
  year={2014},
  volume={19},
  pages={29-37}
}
Most of the traditional medical image fusion methods that use the multi-scale decomposition schemes suffer from the bad image representations and the loss of the dependency in different highpass subbands. To deal with these problems, a novel dependency model, named Explicit Generalized Gaussian Density Dependency (EGGDD) model, is developed by the shift-invariant shearlet transform (SIST). Substantially different from describing the dependency by two hidden states in the Hidden Markov Tree (HMT… CONTINUE READING

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