Title
A multicomponent image segmentation frameworkA multicomponent image segmentation framework
Author
Faculty/Department
Faculty of Sciences. Physics
Research group
Vision lab
Publication type
bookPart
Publication
Berlin :Springer, [*]
Subject
Physics
Source (book)
Advanced concepts for intelligent vision systems / Blanc-Talon, J. [edit.]; et al. [edit.]
ISI
000262163800053
ISBN - Hoofdstuk
978-3-540-88457-6
Carrier
E
Target language
English (eng)
Affiliation
University of Antwerp
Abstract
In this paper, we propose a framework for the segmentation of multicomponent images. The specific framework we aim at contains different steps in which all components of the multicomponent image are processed simultaneoulsy, accounting for the correlation between the image components. The framework contains the following steps: a) to initiate a pixel-based, spectral clustering procedure is applied. b) to include spatial information, a model-based region-merging technique is used, applying a multinormal model for the coefficient regions, and estimating the model parameters using Maximum Likelihood principles; c)the model allows to treat noise that might be present efficiently; d) a multiscale version of the framework is established by repeating the same procedure at different resolution levels of the original image. e) Then, a link between the different levels is established by constructing a hierarchy between the regions at different levels. In this work, we will demonstrate the performance of the framework for segmentation purposes. The procedure is performed on color images and multispectral remote sensing images.
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