Morphological Exponential Entropy Driven-HUM

Risultato della ricerca: Other

1 Citazioni (Scopus)

Abstract

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
Lingua originaleEnglish
Pagine3771-3774
Numero di pagine4
Stato di pubblicazionePublished - 2006

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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