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

Abstract

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… (More)
DOI: 10.1016/j.inffus.2013.04.005

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Cite this paper

@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} }