Gaussian noise image restoration using local statistics
We propose an efficient noise estimation-based method in removing Gaussian noise using local statistics. A proposed detector flexibly classifies the serious and mild noisy pixels prior to applying the strong and weak filters respectively.
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Tagungsbericht |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 150 |
|---|---|
| container_issue | |
| container_start_page | 149 |
| container_title | |
| container_volume | |
| creator | Nguyen, Tuan-Anh Hong, Min-Cheol |
| description | We propose an efficient noise estimation-based method in removing Gaussian noise using local statistics. A proposed detector flexibly classifies the serious and mild noisy pixels prior to applying the strong and weak filters respectively. |
| doi_str_mv | 10.1109/ICCE.2013.6486835 |
| format | Conference Proceeding |
| fullrecord | <record><control><sourceid>proquest_6IE</sourceid><recordid>TN_cdi_proquest_miscellaneous_1786174793</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6486835</ieee_id><sourcerecordid>1786174793</sourcerecordid><originalsourceid>FETCH-LOGICAL-i123t-8e68c0ec80f92e3d4e5fc943e8bd09be86118a46bdb1afbaa9c16eda378ee7c93</originalsourceid><addsrcrecordid>eNpFkE9Lw0AQxdd_YFv9AOIlRy-pO9nN7s5RQq2Fghc9h81mUlbSpGaSg9_egAVPD-b9eMx7QjyAXANIfN4VxWadSVBro51xKr8QS9DGKlAmw0uxyCB3qZYSrv4NkNdnQyHqW7Fk_poJxBwXwm79xBx9l3R9ZEri0R8oGYjHfvBj7Ltk4tgdkrYPvk14nG88xsB34qbxLdP9WVfi83XzUbyl-_ftrnjZpxEyNaaOjAuSgpMNZqRqTXkTUCtyVS2xImcAnNemqivwTeU9BjBUe2UdkQ2oVuLpL_c09N_T_FZ5jByobX1H_cQl2DnCaotqRh__0EhE5WmYqww_5Xko9QsOeVkk</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype><pqid>1786174793</pqid></control><display><type>conference_proceeding</type><title>Gaussian noise image restoration using local statistics</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Nguyen, Tuan-Anh ; Hong, Min-Cheol</creator><creatorcontrib>Nguyen, Tuan-Anh ; Hong, Min-Cheol</creatorcontrib><description>We propose an efficient noise estimation-based method in removing Gaussian noise using local statistics. A proposed detector flexibly classifies the serious and mild noisy pixels prior to applying the strong and weak filters respectively.</description><identifier>ISSN: 2158-3994</identifier><identifier>ISBN: 1467313610</identifier><identifier>ISBN: 9781467313612</identifier><identifier>EISSN: 2158-4001</identifier><identifier>EISBN: 1467313629</identifier><identifier>EISBN: 9781467313636</identifier><identifier>EISBN: 1467313637</identifier><identifier>EISBN: 9781467313629</identifier><identifier>DOI: 10.1109/ICCE.2013.6486835</identifier><language>eng</language><publisher>IEEE</publisher><subject>Classification ; Conferences ; Consumption ; Detectors ; Electronics ; Gaussian ; Gaussian noise ; Information filtering ; Noise ; Noise measurement ; Pixels ; PSNR ; Statistics</subject><ispartof>2013 IEEE International Conference on Consumer Electronics (ICCE), 2013, p.149-150</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6486835$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,314,776,780,785,786,2052,27901,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6486835$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Nguyen, Tuan-Anh</creatorcontrib><creatorcontrib>Hong, Min-Cheol</creatorcontrib><title>Gaussian noise image restoration using local statistics</title><title>2013 IEEE International Conference on Consumer Electronics (ICCE)</title><addtitle>ICCE</addtitle><description>We propose an efficient noise estimation-based method in removing Gaussian noise using local statistics. A proposed detector flexibly classifies the serious and mild noisy pixels prior to applying the strong and weak filters respectively.</description><subject>Classification</subject><subject>Conferences</subject><subject>Consumption</subject><subject>Detectors</subject><subject>Electronics</subject><subject>Gaussian</subject><subject>Gaussian noise</subject><subject>Information filtering</subject><subject>Noise</subject><subject>Noise measurement</subject><subject>Pixels</subject><subject>PSNR</subject><subject>Statistics</subject><issn>2158-3994</issn><issn>2158-4001</issn><isbn>1467313610</isbn><isbn>9781467313612</isbn><isbn>1467313629</isbn><isbn>9781467313636</isbn><isbn>1467313637</isbn><isbn>9781467313629</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2013</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpFkE9Lw0AQxdd_YFv9AOIlRy-pO9nN7s5RQq2Fghc9h81mUlbSpGaSg9_egAVPD-b9eMx7QjyAXANIfN4VxWadSVBro51xKr8QS9DGKlAmw0uxyCB3qZYSrv4NkNdnQyHqW7Fk_poJxBwXwm79xBx9l3R9ZEri0R8oGYjHfvBj7Ltk4tgdkrYPvk14nG88xsB34qbxLdP9WVfi83XzUbyl-_ftrnjZpxEyNaaOjAuSgpMNZqRqTXkTUCtyVS2xImcAnNemqivwTeU9BjBUe2UdkQ2oVuLpL_c09N_T_FZ5jByobX1H_cQl2DnCaotqRh__0EhE5WmYqww_5Xko9QsOeVkk</recordid><startdate>201301</startdate><enddate>201301</enddate><creator>Nguyen, Tuan-Anh</creator><creator>Hong, Min-Cheol</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope></search><sort><creationdate>201301</creationdate><title>Gaussian noise image restoration using local statistics</title><author>Nguyen, Tuan-Anh ; Hong, Min-Cheol</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i123t-8e68c0ec80f92e3d4e5fc943e8bd09be86118a46bdb1afbaa9c16eda378ee7c93</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Classification</topic><topic>Conferences</topic><topic>Consumption</topic><topic>Detectors</topic><topic>Electronics</topic><topic>Gaussian</topic><topic>Gaussian noise</topic><topic>Information filtering</topic><topic>Noise</topic><topic>Noise measurement</topic><topic>Pixels</topic><topic>PSNR</topic><topic>Statistics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nguyen, Tuan-Anh</creatorcontrib><creatorcontrib>Hong, Min-Cheol</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Nguyen, Tuan-Anh</au><au>Hong, Min-Cheol</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Gaussian noise image restoration using local statistics</atitle><btitle>2013 IEEE International Conference on Consumer Electronics (ICCE)</btitle><stitle>ICCE</stitle><date>2013-01</date><risdate>2013</risdate><spage>149</spage><epage>150</epage><pages>149-150</pages><issn>2158-3994</issn><eissn>2158-4001</eissn><isbn>1467313610</isbn><isbn>9781467313612</isbn><eisbn>1467313629</eisbn><eisbn>9781467313636</eisbn><eisbn>1467313637</eisbn><eisbn>9781467313629</eisbn><abstract>We propose an efficient noise estimation-based method in removing Gaussian noise using local statistics. A proposed detector flexibly classifies the serious and mild noisy pixels prior to applying the strong and weak filters respectively.</abstract><pub>IEEE</pub><doi>10.1109/ICCE.2013.6486835</doi><tpages>2</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 2158-3994 |
| ispartof | 2013 IEEE International Conference on Consumer Electronics (ICCE), 2013, p.149-150 |
| issn | 2158-3994 2158-4001 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1786174793 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Classification Conferences Consumption Detectors Electronics Gaussian Gaussian noise Information filtering Noise Noise measurement Pixels PSNR Statistics |
| title | Gaussian noise image restoration using local statistics |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-10T07%3A19%3A16IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Gaussian%20noise%20image%20restoration%20using%20local%20statistics&rft.btitle=2013%20IEEE%20International%20Conference%20on%20Consumer%20Electronics%20(ICCE)&rft.au=Nguyen,%20Tuan-Anh&rft.date=2013-01&rft.spage=149&rft.epage=150&rft.pages=149-150&rft.issn=2158-3994&rft.eissn=2158-4001&rft.isbn=1467313610&rft.isbn_list=9781467313612&rft_id=info:doi/10.1109/ICCE.2013.6486835&rft_dat=%3Cproquest_6IE%3E1786174793%3C/proquest_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=1467313629&rft.eisbn_list=9781467313636&rft.eisbn_list=1467313637&rft.eisbn_list=9781467313629&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1786174793&rft_id=info:pmid/&rft_ieee_id=6486835&rfr_iscdi=true |