Multi-frame blind deconvolution of atmospheric turbulence degraded images with mixed noise models
Yang, Afeng and Jiang, Xue and Day-Uei Li, David (2018) Multi-frame blind deconvolution of atmospheric turbulence degraded images with mixed noise models. Electronics Letters, 54 (4). pp. 206-208. ISSN 0013-5194 (https://doi.org/10.1049/el.2017.4277)
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Abstract
This paper proposes a mixed noise model and uses the multi-frame blind deconvolution to restore the images of space objects under the Bayesian inference framework. To minimize the cost function, an algorithm based on iterative recursion was proposed. In addition, three limited bandwidth constraints of the point spread functions were imposed into the solution process to avoid converging to local minima. Experimental results show that the proposed algorithm can effectively restore the turbulence degraded images and alleviate the distortion caused by the noise.
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Item type: Article ID code: 62591 Dates: DateEvent27 February 2018Published7 December 2017Published Online6 December 2017AcceptedNotes: This paper is a postprint of a paper submitted to and accepted for publication in Electronics Letters and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at the IET Digital Library. Subjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Naval Architecture, Ocean & Marine Engineering
Strategic Research Themes > Health and Wellbeing
Faculty of Science > Strathclyde Institute of Pharmacy and Biomedical SciencesDepositing user: Pure Administrator Date deposited: 12 Dec 2017 14:20 Last modified: 07 Aug 2024 01:30 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/62591
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