title: Morphological exponential entropy driven-HUM.
abstract: This paper presents an improvement to the exponential entropy driven-homomorphic unsharp masking (E(2)D-HUM) algorithm devoted to illumination artifact suppression on magnetic resonance images. E(2)D-HUM requires a segmentation step to remove dark regions in the foreground whose intensity is comparable with background, because strong edges produce streak artifacts on the tissues. This new version of the algorithm keeps the same good properties of E(2)D-HUM without a segmentation phase, whose parameters should be chosen in relation to the image.
authors.affiliation: Dept. of Comput. Sci., Palermo Univ. ardizzon@unipa.it
authors.forename: Edoardo
authors.initials: E
authors.lastname: Ardizzone
authors.forename: Roberto
authors.initials: R
authors.lastname: Pirrone
authors.forename: Orazio
authors.initials: O
authors.lastname: Gambino
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000033:anatomy & histology* / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D019277:Entropy; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008959:Models, Neurological