Image quality metrics based multifocus image fusion

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contributor.author Saleem, A en_US
contributor.author Beghdadi, A en_US
contributor.author Boashash, B en_US
date.accessioned 2012-06-18T08:42:50Z en_US
date.available 2012-06-18T08:42:50Z en_US
date.issued 2011 en_US
identifier.citation A. Saleem, A. Beghdadi, and B. Boashash, "Image quality metrics based multifocus image fusion," in Proc. 3rd European Workshop on Visual Information Processing (EUVIP), 2011, pp. 77-82 en_US
identifier.uri http://dx.doi.org/10.1109/EuVIP.2011.6045547 en_US
identifier.uri http://hdl.handle.net/10576/10848 en_US
description This paper presents a novel block based multi-focus image fusion method to utilize blur image quality metrics to guide the multi-focus image fusion problem in the spatial domain. (Additional details can be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (see http://www.elsevier.com/locate/isbn/0080443354). In addition, the most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated). en_US
description.abstract We describe an innovative methodology for block based multifocus image fusion in the spatial domain. The main idea is to use blind or no reference blur metrics for image fusion applications. Two blur quality metrics based on edge content information and radon wigner ville based mean directional entropy, developed in the paper are used as activity measures. Fusion is performed by calculating blur based activity measure for each sub window in the source images and using maximum selection criterion according to the magnitude of these metrics. Furthermore, the defined metrics can be used for quantitative performance assessment of multifiocus fused images. The results of the proposed algorithm are compared to some existing image fusion methods. en_US
language.iso en en_US
publisher IEEE en_US
subject image fusion en_US
subject image quality en_US
subject performance evaluation en_US
subject Radon-Wigner-Ville based mean directional entropy en_US
subject blur quality metrics en_US
subject edge content information en_US
subject image quality metrics en_US
subject maximum selection criterion en_US
subject multifocus image fusion en_US
subject quantitative performance assessment en_US
title Image quality metrics based multifocus image fusion en_US
type Conference Paper en_US


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