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|a 10.1109/TIP.2012.2189577
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|a eng
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|a Zhou, Zhe
|e verfasserin
|4 aut
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|a Cognition and removal of impulse noise with uncertainty
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|c 2012
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|a Text
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|a ƒaComputermedien
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|a Date Completed 15.10.2012
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|a Date Revised 19.06.2012
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a Uncertainties are the major inherent feature of impulse noise. This fact makes image denoising a difficult task. Understanding the uncertainties can improve the performance of image denoising. This paper presents a novel adaptive detail-preserving filter based on the cloud model (CM) to remove impulse noise. It is called the CM filter. First, an uncertainty-based detector identifies the pixels corrupted by impulse noise. Then, a weighted fuzzy mean filter is applied to remove the noise candidates. The experimental results show that, compared with the traditional switching filters, the CM filter makes a great improvement in image denoising. Even at a noise level as high as 95%, the CM filter still can restore the image with good detail preservation
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|a Journal Article
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|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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|g 21(2012), 7 vom: 16. Juli, Seite 3157-67
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