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231224s2014 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2014.2347204
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|a eng
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| 100 |
1 |
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|a Liu, Xinhao
|e verfasserin
|4 aut
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| 245 |
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|a Practical signal-dependent noise parameter estimation from a single noisy image
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|c 2014
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|a Text
|b txt
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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| 500 |
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|a Date Completed 30.03.2015
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|a Date Revised 06.09.2014
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a The additive white Gaussian noise is widely assumed in many image processing algorithms. However, in the real world, the noise from actual cameras is better modeled as signal-dependent noise (SDN). In this paper, we focus on the SDN model and propose an algorithm to automatically estimate its parameters from a single noisy image. The proposed algorithm identifies the noise level function of signal-dependent noise assuming the generalized signal-dependent noise model and is also applicable to the Poisson-Gaussian noise model. The accuracy is achieved by improved estimation of local mean and local noise variance from the selected low-rank patches. We evaluate the proposed algorithm with both synthetic and real noisy images. Experiments demonstrate that the proposed estimation algorithm outperforms the state-of-the-art methods
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|a Journal Article
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| 700 |
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|a Tanaka, Masayuki
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Okutomi, Masatoshi
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 23(2014), 10 vom: 03. Okt., Seite 4361-71
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|g volume:23
|g year:2014
|g number:10
|g day:03
|g month:10
|g pages:4361-71
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|u http://dx.doi.org/10.1109/TIP.2014.2347204
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