Image complexity based impulse noise filter

碩士 === 淡江大學 === 機械與機電工程學系碩士班 === 99 === In this thesis, we propose an image complexity based impulse noise filter. We distinguish smooth or complex regions by standard deviation and histogram of the corrupted image. By simulation result, SWM-I and SWM-II filter have better capability in the smooth a...

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Main Authors: Li-Wun Hu, 胡力文
Other Authors: 孫崇訓
Format: Others
Language:zh-TW
Published: 2011
Online Access:http://ndltd.ncl.edu.tw/handle/61941218011687220663
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spelling ndltd-TW-099TKU054890202016-04-11T04:22:23Z http://ndltd.ncl.edu.tw/handle/61941218011687220663 Image complexity based impulse noise filter 基於影像複雜度之脈衝雜訊濾波器 Li-Wun Hu 胡力文 碩士 淡江大學 機械與機電工程學系碩士班 99 In this thesis, we propose an image complexity based impulse noise filter. We distinguish smooth or complex regions by standard deviation and histogram of the corrupted image. By simulation result, SWM-I and SWM-II filter have better capability in the smooth and complex region, respectively. Therefore, we incorporate the SWM-I and SWM-II filter into a noise detection mechanism to determine whether a pixel is corrupted. According to the proposed method, a corrupted image can be classed as smooth and complex regions the appropriate filters are selected to process the regions, respectively. Finally, we calculate Peak-Signal-to-Noise Ratio of filtered image to perform noise removal capability. 孫崇訓 2011 學位論文 ; thesis 55 zh-TW
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description 碩士 === 淡江大學 === 機械與機電工程學系碩士班 === 99 === In this thesis, we propose an image complexity based impulse noise filter. We distinguish smooth or complex regions by standard deviation and histogram of the corrupted image. By simulation result, SWM-I and SWM-II filter have better capability in the smooth and complex region, respectively. Therefore, we incorporate the SWM-I and SWM-II filter into a noise detection mechanism to determine whether a pixel is corrupted. According to the proposed method, a corrupted image can be classed as smooth and complex regions the appropriate filters are selected to process the regions, respectively. Finally, we calculate Peak-Signal-to-Noise Ratio of filtered image to perform noise removal capability.
author2 孫崇訓
author_facet 孫崇訓
Li-Wun Hu
胡力文
author Li-Wun Hu
胡力文
spellingShingle Li-Wun Hu
胡力文
Image complexity based impulse noise filter
author_sort Li-Wun Hu
title Image complexity based impulse noise filter
title_short Image complexity based impulse noise filter
title_full Image complexity based impulse noise filter
title_fullStr Image complexity based impulse noise filter
title_full_unstemmed Image complexity based impulse noise filter
title_sort image complexity based impulse noise filter
publishDate 2011
url http://ndltd.ncl.edu.tw/handle/61941218011687220663
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AT húlìwén jīyúyǐngxiàngfùzádùzhīmàichōngzáxùnlǜbōqì
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