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Title: ppt on noise control of ic engine
Page Link: ppt on noise control of ic engine -
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Created at: Sunday 30th of September 2012 09:34:09 PM
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Title: noise reduction in ic engine pdf with ppt
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Created at: Saturday 26th of January 2013 11:59:41 AM
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Title: advantages and disadvantages of noise control in ic engine
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Created at: Wednesday 09th of October 2013 09:16:27 PM
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Title: noise and vibration control in ic engine seminars pdf
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Created at: Sunday 27th of March 2016 02:16:38 PM
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Title: ppt on noise control of ic engine
Page Link: ppt on noise control of ic engine -
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Created at: Sunday 30th of September 2012 09:24:52 PM
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Title: matlab code for salt and pepper noise removal by median type noise detectors and detail preserving regularization
Page Link: matlab code for salt and pepper noise removal by median type noise detectors and detail preserving regularization -
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Created at: Monday 22nd of July 2013 12:01:29 AM
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Title: research paper on noise control in i c engine
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Created at: Wednesday 03rd of October 2012 10:10:18 PM
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Title: noise control in ic engine pdf research papers
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Created at: Wednesday 05th of August 2015 12:57:49 AM
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Title: abstract part of a paper on noise control in ic engine
Page Link: abstract part of a paper on noise control in ic engine -
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Created at: Friday 12th of October 2012 10:04:22 PM
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Title: Salt-and-Pepper Noise Removal by Median-type Noise Detectors and Detail-preserving
Page Link: Salt-and-Pepper Noise Removal by Median-type Noise Detectors and Detail-preserving -
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Created at: Saturday 07th of May 2011 01:35:21 PM
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Abstract
This paper proposes a two-phase scheme for removing salt-and-pepper impulse noise. In the first
phase, an adaptive median filter is used to identify pixels which are likely to be contaminated by noise
(noise candidates). In the second phase, the image is restored using a specialized regularization method
that applies only to those selected noise candidates. In terms of edge preservation and noise suppression,
our restored images show a significant improvement compared to those restored by using just nonlinear
filters or r ....etc
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