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Abstract: Many imaging systems rely on photon detection as the basis of image formation. One of the major sources of error in these imaging systems is Poisson noise due to the quantum nature of the photon detection process. Unlike additive Gaussian noise, Poisson noise is signal-dependent, and consequently separating signal from noise is a very difficult task. In this paper, we develop a novel wavelet-domain filtering procedure for noise removal in photon imaging systems. The filter adapts to both... (Update)
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...image modeling using stochastic model has been widely studied and used in various image processing applications. See something [5, 12, 11, 2]. 2 Adaptive Wiener filtering 2.1 Wiener filter Suppose a signal s(m; n) is polluted by an additive noise w(m;n) and we wish to...
...can be detected using nuclear medicine image before they will show up in X ray images. More information on this data can be found in [41]. The hereditary Haar and platelet based MPLEs are shown below below. The first set of estimates (Figures 6 (b) d) g) and (i) were...
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BibTeX entry: (Update)
@misc{ department-waveletdomain,
author = "Robert Nowak Department",
title = "Wavelet-Domain Filtering for Photon Imaging Systems",
url = "citeseer.ist.psu.edu/nowak97waveletdomain.html" }
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13 A new class of of unbalanced haar wavelets that form an unco.. - Girardi, Sweldens - 1997
11 Optimal signal estimation using cross-validation - Nowak - 1996
9 Objective assessment of image quality: effects of quantum no.. (context) - Barrett - 1990
6 Wavelet domain filtering for nuclear medicine imaging - Nowak, Hellman et al. - 1996
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4 New York: Grune & Stratton (context) - Sorenson, Phelps et al. - 1980
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4 MA: Wellsley-Cambridge (context) - Strang, Nguyen et al. - 1996
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