Novel speckle remove method based on ASUSAN nonlinear diffusion
As we all know, speckle noise exist in ultrasound and radar images, and it brings bad affection to image analysis, like image segmentation, image fusion and image registration. So far, many diffusion methods have been put forward to remove speckle noise, but they all have some defections because the...
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| creator | Shen Minfen Xu Yugui |
| description | As we all know, speckle noise exist in ultrasound and radar images, and it brings bad affection to image analysis, like image segmentation, image fusion and image registration. So far, many diffusion methods have been put forward to remove speckle noise, but they all have some defections because their diffusion models are unsuitable for speckle noise. In this paper, a novel speckle remove method based on ASUSAN nonlinear diffusion is proposed. We adopt SUSAN operator to detect image edges, then k-means algorithm is used to select fully formed speckle region, finally our ASUSAN diffusion method is obtained to remove speckle noise by iterations. The experiments demonstrate that our proposed method achieves better results in PSNR, MES, FOM and image edges preserve, compared with the other methods. |
| doi_str_mv | 10.1109/ICEMI.2013.6743020 |
| format | Conference Proceeding |
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So far, many diffusion methods have been put forward to remove speckle noise, but they all have some defections because their diffusion models are unsuitable for speckle noise. In this paper, a novel speckle remove method based on ASUSAN nonlinear diffusion is proposed. We adopt SUSAN operator to detect image edges, then k-means algorithm is used to select fully formed speckle region, finally our ASUSAN diffusion method is obtained to remove speckle noise by iterations. 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So far, many diffusion methods have been put forward to remove speckle noise, but they all have some defections because their diffusion models are unsuitable for speckle noise. In this paper, a novel speckle remove method based on ASUSAN nonlinear diffusion is proposed. We adopt SUSAN operator to detect image edges, then k-means algorithm is used to select fully formed speckle region, finally our ASUSAN diffusion method is obtained to remove speckle noise by iterations. The experiments demonstrate that our proposed method achieves better results in PSNR, MES, FOM and image edges preserve, compared with the other methods.</description><subject>Adaptation models</subject><subject>adaptive SUSAN</subject><subject>anisotropic diffusion</subject><subject>Anisotropic magnetoresistance</subject><subject>Computational modeling</subject><subject>FFS region</subject><subject>Image edge detection</subject><subject>K-mean</subject><subject>Mathematical model</subject><subject>Noise</subject><subject>Speckle</subject><subject>speckle remove</subject><isbn>147990757X</isbn><isbn>9781479907571</isbn><isbn>1479907588</isbn><isbn>9781479907595</isbn><isbn>1479907596</isbn><isbn>9781479907588</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2013</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpFj81Kw0AURkdEUNu-gG7mBRLvZCa5MysJoWqgtotWcFeSzB0czU_JVMG3N2LBb_NxNgcOYzcCYiHA3JXF8rmMExAyzlBJSOCMXQuFxgCmWp__A75eskUI7wAgEBOdySt2vx6-qOXhQM1HS3ykbmLe0fFtsLyuAlk-9DzfvmzzNe-HvvU9VSO33rnP4Id-zi5c1QZanH7Gdg_LXfEUrTaPZZGvIm_gGKU2VQ0l1iisaq2pQZs0E7jaohFgwWSU2akGVY3kgJxyRgOhA_ydnLHbP60nov1h9F01fu9PvfIHsf1JPg</recordid><startdate>201308</startdate><enddate>201308</enddate><creator>Shen Minfen</creator><creator>Xu Yugui</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201308</creationdate><title>Novel speckle remove method based on ASUSAN nonlinear diffusion</title><author>Shen Minfen ; Xu Yugui</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-5d54ce2d947ab88ec7d2c947fbd7910d096e6d10974b7ef0ef4f980e7f0777773</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Adaptation models</topic><topic>adaptive SUSAN</topic><topic>anisotropic diffusion</topic><topic>Anisotropic magnetoresistance</topic><topic>Computational modeling</topic><topic>FFS region</topic><topic>Image edge detection</topic><topic>K-mean</topic><topic>Mathematical model</topic><topic>Noise</topic><topic>Speckle</topic><topic>speckle remove</topic><toplevel>online_resources</toplevel><creatorcontrib>Shen Minfen</creatorcontrib><creatorcontrib>Xu Yugui</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Shen Minfen</au><au>Xu Yugui</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Novel speckle remove method based on ASUSAN nonlinear diffusion</atitle><btitle>2013 IEEE 11th International Conference on Electronic Measurement & Instruments</btitle><stitle>ICEMI</stitle><date>2013-08</date><risdate>2013</risdate><volume>1</volume><spage>23</spage><epage>27</epage><pages>23-27</pages><isbn>147990757X</isbn><isbn>9781479907571</isbn><eisbn>1479907588</eisbn><eisbn>9781479907595</eisbn><eisbn>1479907596</eisbn><eisbn>9781479907588</eisbn><abstract>As we all know, speckle noise exist in ultrasound and radar images, and it brings bad affection to image analysis, like image segmentation, image fusion and image registration. So far, many diffusion methods have been put forward to remove speckle noise, but they all have some defections because their diffusion models are unsuitable for speckle noise. In this paper, a novel speckle remove method based on ASUSAN nonlinear diffusion is proposed. We adopt SUSAN operator to detect image edges, then k-means algorithm is used to select fully formed speckle region, finally our ASUSAN diffusion method is obtained to remove speckle noise by iterations. The experiments demonstrate that our proposed method achieves better results in PSNR, MES, FOM and image edges preserve, compared with the other methods.</abstract><pub>IEEE</pub><doi>10.1109/ICEMI.2013.6743020</doi><tpages>5</tpages></addata></record> |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Adaptation models adaptive SUSAN anisotropic diffusion Anisotropic magnetoresistance Computational modeling FFS region Image edge detection K-mean Mathematical model Noise Speckle speckle remove |
| title | Novel speckle remove method based on ASUSAN nonlinear diffusion |
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