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Image identification and restoration using EM algorithm

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dc.contributor Graduate Program in Electrical and Electronic Engineering.
dc.contributor.advisor Anarım, Emin.
dc.contributor.advisor Istefanopulos, Yorgo.
dc.contributor.author Yemez, Yücel.
dc.date.accessioned 2023-03-16T10:22:07Z
dc.date.available 2023-03-16T10:22:07Z
dc.date.issued 1992.
dc.identifier.other EE 1992 Y39
dc.identifier.uri http://digitalarchive.boun.edu.tr/handle/123456789/13058
dc.description.abstract This thesis considers the problem of identification and restoration of images degraded by additive Gaussian white noise. It is assumed that the power of the noise and the statistical properties of the original image are not known a priori. A new approach which reduces the two dimensional problem to a one dimensional problem by using the unitary discrete Fourier transform is introduced. Then, by applying the expectation-maximization (EM) algorithm, the image is restored and the parameters of various types of AR models are identified under noisy conditions. Two different methods are used for restoration, namely, maximum likelihood restoration and Kalman filtering. The simulation results of the presented approach are also included.
dc.format.extent 30 cm.
dc.publisher Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 1992.
dc.relation Includes appendices.
dc.relation Includes appendices.
dc.subject.lcsh Expectation-maximization algorithms.
dc.subject.lcsh Image processing.
dc.subject.lcsh Kalman filtering.
dc.subject.lcsh Autoregression (Statistics)
dc.title Image identification and restoration using EM algorithm
dc.format.pages xiii, 56 leaves;


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