Open AccessImproved probabilistic pseudo‐morphology for noise reduction in colour images
Author(s) -
Coliban RaduMihai,
Ivanovici Mihai,
Richard Noël
Publication year - 2016
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2015.0741
Subject(s) - mathematical morphology , probabilistic logic , artificial intelligence , computer science , pattern recognition (psychology) , multivariate statistics , noise reduction , maxima and minima , context (archaeology) , noise (video) , pyramid (geometry) , reduction (mathematics) , computer vision , filter (signal processing) , binary image , image processing , binary number , median filter , image (mathematics) , mathematics , machine learning , geography , mathematical analysis , geometry , arithmetic , archaeology
Mathematical morphology is a popular framework for non‐linear image processing, first introduced for binary and grey‐level images, then extended to colour and multivariate images. Various pseudo‐morphologies have been proposed as solutions to the problem of ordering multivariate data. Despite the lack of some properties, pseudo‐morphologies have proved useful in various applications, such as filtering or texture classification. The authors propose to improve the existing colour probabilistic pseudo‐morphology by changing the way the local pseudo‐extrema are chosen. They show the usefulness of the new construction in the context of noise reduction in colour images using the open‐close close‐open filter, by highlighting the improvement over the original construction and comparing the authors’ results with other relevant morphological and pseudo‐morphological approaches.