• May 15, 2019 News!Vol.7, No.5- Vol.8, No.4 has been indexed by EI (Inspec).   [Click]
  • Aug 01, 2018 News! [CFP] 2020 the annual meeting of IJMO Editorial Board, ECDMO 2020, will be held in Athens, Greece, February 15-17, 2020.   [Click]
  • Sep 30, 2019 News!Vol 9, No 6 has been published with online version. 12 original aritcles from 6 countries are published in this issue.    [Click]
General Information
    • ISSN: 2010-3697  (Online)
    • Abbreviated Title: Int. J. Model. Optim.
    • Frequency: Bimonthly
    • DOI: 10.7763/IJMO
    • Editor-in-Chief: Prof. Adrian Olaru
    • Executive Editor: Ms.Yoyo Y. Zhou
    • Abstracting/ Indexing: ProQuest, Crossref, Electronic Journals Library, Google Scholar, EI (INSPEC, IET), EBSCO, etc.
    • E-mail ijmo@iacsitp.com
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2012 Vol.2(4): 378-383 ISSN: 2010-3697
DOI: 10.7763/IJMO.2012.V2.147

Comparative and Quantitative Study of Fundamental Approaches on Digital Aerial Image Deblurring

Z. Mao Ye and H. Mohamadian

Abstract—Digital image deblurring is a classical real-world problem with applications ranging from astronomy to photography. For aerial digital images, image blurring is inevitable due to object moving, platform moving and possible camera shaking. Image deblurring is to estimate the actual scene by sharpening the observed images being blurred or corrupted by any motion. At the same time, it aims to retain important object features as much as possible. It plays an important role in information decision support systems. There are many numerical filtering, deconvolution and optimization approaches to sharpen the blurry images. Certain approaches even combine with implementation of artificial intelligence. Some of them are in fact very complicated in theory and practice. This article applies several fundamental methods to aerial image deblurring. Satisfactory results on each level of true color aerial images are obtained with ease using these fundamental technologies. In addition, quantitative measures are proposed to evaluate the outcomes in an objective manner, where metrics of discrete entropy, relative entropy, discrete energy, mutual information, contrast and homogeneity are introduced for evaluating aerial image deblurring. This approach has the potential for accurate decision making.

Index Terms—Image deblurring, deconvolution, filtering, optimization, quantitative analysis.

Z. Ye and H. Mohamadian are with Southern University, Baton Rouge, Louisiana 70813, USA (e-mail: zhengmao_ye@subr.edu; habib_mohamadian@subr.edu).
H. Mohamadian is with Southern University, Baton Rouge, Louisiana70813, USA (e-mail: habib_mohamadian@subr.edu).


Cite: Z. Mao Ye and H. Mohamadian, "Comparative and Quantitative Study of Fundamental Approaches on Digital Aerial Image Deblurring," International Journal of Modeling and Optimization vol. 2, no. 4, pp. 378-383, 2012.

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