Morphological Exponential Entropy Driven-HUM
- Autori: Ardizzone, E.; Pirrone, R.; Gambino, O.
- Anno di pubblicazione: 2006
- Tipologia: Proceedings (TIPOLOGIA NON ATTIVA)
This paper presents an improvement to the exponential entropy driven-homomorphic unsharp masking (E2D-HUM) algorithm devoted to illumination artifact suppression on magnetic resonance images. E2D-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 E2D-HUM without a segmentation phase, whose parameters should be chosen in relation to the image