Improved probabilistic pseudo‐morphology for noise reduction in colour images. Issue 7 (1st July 2016)

• Record Type: Journal Article
• Authors: Coliban, Radu‐Mihai; Ivanovici, Mihai; Richard, Noël
• Is Part Of: IET image processing. Volume 10:Issue 7(2016)
• Page Start: 505
• Page End: 514
• Publication Date: 2016-07-01
• Subjects: image colour analysis -- probability -- mathematical morphology -- filtering theory; probabilistic pseudo morphology -- noise reduction -- colour images -- mathematical morphology -- nonlinear image processing -- grey level images -- binary images -- multivariate images -- ordering multivariate data -- colour probabilistic pseudo morphology -- open‐close close‐open filter; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2015.0741
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : 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.