Edge Preserving Image Denoising in Reproducing Kernel Hilbert Spaces
The goal of this paper is the development of a novel approach for the problem of Noise Removal, based on the theory of Reproducing Kernels Hilbert Spaces (RKHS). The problem is cast as an optimization task in a RKHS, by taking advantage of the celebrated semi parametric Representer Theorem. Examples...
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| creator | Bouboulis, P Theodoridis, S Slavakis, K |
| description | The goal of this paper is the development of a novel approach for the problem of Noise Removal, based on the theory of Reproducing Kernels Hilbert Spaces (RKHS). The problem is cast as an optimization task in a RKHS, by taking advantage of the celebrated semi parametric Representer Theorem. Examples verify that in the presence of gaussian noise the proposed method performs relatively well compared to wavelet based techniques and outperforms them significantly in the presence of impulse or mixed noise. |
| doi_str_mv | 10.1109/ICPR.2010.652 |
| format | Conference Proceeding |
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Examples verify that in the presence of gaussian noise the proposed method performs relatively well compared to wavelet based techniques and outperforms them significantly in the presence of impulse or mixed noise.</description><subject>Hilbert space</subject><subject>Image denoising</subject><subject>Image edge detection</subject><subject>Kernel</subject><subject>Noise</subject><subject>Noise reduction</subject><subject>Pixel</subject><issn>1051-4651</issn><issn>2831-7475</issn><isbn>1424475422</isbn><isbn>9781424475421</isbn><isbn>9781424475414</isbn><isbn>9780769541099</isbn><isbn>1424475414</isbn><isbn>0769541097</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1zktLw1AQBeDrC6w1S1du8gdSZ-a-kqWk1QYLltp9uUkm5UKahpsq-O9NUVfDdw4cRogHhBkiZE9Fvt7MCEYaTRciymyKipSyWqG6FBNKJSZ25JW4-y-IrsUEQWOijMZbEQ2DL4GMNVZrPRHzRb3neB144PDlu31cHNwYzLk7-uFs38Ub7sOx_qzOfOPQcRsvfVtyOMUfvat4uBc3jWsHjv7uVGxfFtt8mazeX4v8eZX4DE5J6kxGlmUKJajKKlYobdVUTdrUaDWbmlMgGt9sMkDDkhpCJqcQKnBKyql4_J31zLzrgz-48L3TOjOAKH8A3RNNiA</recordid><startdate>201008</startdate><enddate>201008</enddate><creator>Bouboulis, P</creator><creator>Theodoridis, S</creator><creator>Slavakis, K</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201008</creationdate><title>Edge Preserving Image Denoising in Reproducing Kernel Hilbert Spaces</title><author>Bouboulis, P ; Theodoridis, S ; Slavakis, K</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-8a6927e380b04c74e4137cfcf8fd175e6de8022651f9016e32f21e2a410c0a433</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Hilbert space</topic><topic>Image denoising</topic><topic>Image edge detection</topic><topic>Kernel</topic><topic>Noise</topic><topic>Noise reduction</topic><topic>Pixel</topic><toplevel>online_resources</toplevel><creatorcontrib>Bouboulis, P</creatorcontrib><creatorcontrib>Theodoridis, S</creatorcontrib><creatorcontrib>Slavakis, K</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/IET Electronic Library (IEL)</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>Bouboulis, P</au><au>Theodoridis, S</au><au>Slavakis, K</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Edge Preserving Image Denoising in Reproducing Kernel Hilbert Spaces</atitle><btitle>2010 20th International Conference on Pattern Recognition</btitle><stitle>ICPR</stitle><date>2010-08</date><risdate>2010</risdate><spage>2660</spage><epage>2663</epage><pages>2660-2663</pages><issn>1051-4651</issn><eissn>2831-7475</eissn><isbn>1424475422</isbn><isbn>9781424475421</isbn><eisbn>9781424475414</eisbn><eisbn>9780769541099</eisbn><eisbn>1424475414</eisbn><eisbn>0769541097</eisbn><abstract>The goal of this paper is the development of a novel approach for the problem of Noise Removal, based on the theory of Reproducing Kernels Hilbert Spaces (RKHS). 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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Hilbert space Image denoising Image edge detection Kernel Noise Noise reduction Pixel |
| title | Edge Preserving Image Denoising in Reproducing Kernel Hilbert Spaces |
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