A Blind Restoration Method for Remote Sensing Images
This letter proposes a blind image restoration method for the deblurring of remote sensing images. A simple but robust identification method of point spread function (PSF) support is proposed, and a joint estimation method is presented to simultaneously solve the PSF coefficients and restoration ima...
Gespeichert in:
| Veröffentlicht in: | IEEE geoscience and remote sensing letters 2012-11, Vol.9 (6), p.1137-1141 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 1141 |
|---|---|
| container_issue | 6 |
| container_start_page | 1137 |
| container_title | IEEE geoscience and remote sensing letters |
| container_volume | 9 |
| creator | Shen, Huanfeng Du, Lijun Zhang, Liangpei Gong, Wei |
| description | This letter proposes a blind image restoration method for the deblurring of remote sensing images. A simple but robust identification method of point spread function (PSF) support is proposed, and a joint estimation method is presented to simultaneously solve the PSF coefficients and restoration image. To narrow the solution space for the best possible definition, the Huber-Markov (Huber-Markov random field) prior model is employed to regularize the two series of unknowns. Experiments were performed to demonstrate the effectiveness of the proposed approach. |
| doi_str_mv | 10.1109/LGRS.2012.2190038 |
| format | Article |
| fullrecord | <record><control><sourceid>crossref_RIE</sourceid><recordid>TN_cdi_ieee_primary_6194272</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6194272</ieee_id><sourcerecordid>10_1109_LGRS_2012_2190038</sourcerecordid><originalsourceid>FETCH-LOGICAL-c265t-cc45ce8c833a203648c09ec95f08dc67ea8c6069572e3a3329a8c67f49ec43e53</originalsourceid><addsrcrecordid>eNo9j89KAzEYxIMoWKsPIF7yArt--bvJsRathRWhVfAWQvbbutLdSLIX394uLT3NMMwM_Ai5Z1AyBvaxXm22JQfGS84sgDAXZMaUMgWoil1OXqpCWfN1TW5y_gHg0phqRuSCPu27oaEbzGNMfuziQN9w_I4NbWM6xH0ckW5xyN2wo-ve7zDfkqvW7zPenXROPl-eP5avRf2-Wi8XdRG4VmMRglQBTTBCeA5CSxPAYrCqBdMEXaE3QYO2quIovBDcTkHVykNJClRiTtjxN6SYc8LW_aau9-nPMXATtpuw3YTtTtiHzcNx0yHiua-Zlbzi4h8bs1LC</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>A Blind Restoration Method for Remote Sensing Images</title><source>IEEE Electronic Library (IEL)</source><creator>Shen, Huanfeng ; Du, Lijun ; Zhang, Liangpei ; Gong, Wei</creator><creatorcontrib>Shen, Huanfeng ; Du, Lijun ; Zhang, Liangpei ; Gong, Wei</creatorcontrib><description>This letter proposes a blind image restoration method for the deblurring of remote sensing images. A simple but robust identification method of point spread function (PSF) support is proposed, and a joint estimation method is presented to simultaneously solve the PSF coefficients and restoration image. To narrow the solution space for the best possible definition, the Huber-Markov (Huber-Markov random field) prior model is employed to regularize the two series of unknowns. Experiments were performed to demonstrate the effectiveness of the proposed approach.</description><identifier>ISSN: 1545-598X</identifier><identifier>EISSN: 1558-0571</identifier><identifier>DOI: 10.1109/LGRS.2012.2190038</identifier><identifier>CODEN: IGRSBY</identifier><language>eng</language><publisher>IEEE</publisher><subject>Blind restoration ; Deconvolution ; Estimation ; Image restoration ; joint estimation ; Joints ; Measurement ; Optimized production technology ; Remote sensing ; support identification</subject><ispartof>IEEE geoscience and remote sensing letters, 2012-11, Vol.9 (6), p.1137-1141</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c265t-cc45ce8c833a203648c09ec95f08dc67ea8c6069572e3a3329a8c67f49ec43e53</citedby><cites>FETCH-LOGICAL-c265t-cc45ce8c833a203648c09ec95f08dc67ea8c6069572e3a3329a8c67f49ec43e53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6194272$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6194272$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Shen, Huanfeng</creatorcontrib><creatorcontrib>Du, Lijun</creatorcontrib><creatorcontrib>Zhang, Liangpei</creatorcontrib><creatorcontrib>Gong, Wei</creatorcontrib><title>A Blind Restoration Method for Remote Sensing Images</title><title>IEEE geoscience and remote sensing letters</title><addtitle>LGRS</addtitle><description>This letter proposes a blind image restoration method for the deblurring of remote sensing images. A simple but robust identification method of point spread function (PSF) support is proposed, and a joint estimation method is presented to simultaneously solve the PSF coefficients and restoration image. To narrow the solution space for the best possible definition, the Huber-Markov (Huber-Markov random field) prior model is employed to regularize the two series of unknowns. Experiments were performed to demonstrate the effectiveness of the proposed approach.</description><subject>Blind restoration</subject><subject>Deconvolution</subject><subject>Estimation</subject><subject>Image restoration</subject><subject>joint estimation</subject><subject>Joints</subject><subject>Measurement</subject><subject>Optimized production technology</subject><subject>Remote sensing</subject><subject>support identification</subject><issn>1545-598X</issn><issn>1558-0571</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9j89KAzEYxIMoWKsPIF7yArt--bvJsRathRWhVfAWQvbbutLdSLIX394uLT3NMMwM_Ai5Z1AyBvaxXm22JQfGS84sgDAXZMaUMgWoil1OXqpCWfN1TW5y_gHg0phqRuSCPu27oaEbzGNMfuziQN9w_I4NbWM6xH0ckW5xyN2wo-ve7zDfkqvW7zPenXROPl-eP5avRf2-Wi8XdRG4VmMRglQBTTBCeA5CSxPAYrCqBdMEXaE3QYO2quIovBDcTkHVykNJClRiTtjxN6SYc8LW_aau9-nPMXATtpuw3YTtTtiHzcNx0yHiua-Zlbzi4h8bs1LC</recordid><startdate>20121101</startdate><enddate>20121101</enddate><creator>Shen, Huanfeng</creator><creator>Du, Lijun</creator><creator>Zhang, Liangpei</creator><creator>Gong, Wei</creator><general>IEEE</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20121101</creationdate><title>A Blind Restoration Method for Remote Sensing Images</title><author>Shen, Huanfeng ; Du, Lijun ; Zhang, Liangpei ; Gong, Wei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c265t-cc45ce8c833a203648c09ec95f08dc67ea8c6069572e3a3329a8c67f49ec43e53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Blind restoration</topic><topic>Deconvolution</topic><topic>Estimation</topic><topic>Image restoration</topic><topic>joint estimation</topic><topic>Joints</topic><topic>Measurement</topic><topic>Optimized production technology</topic><topic>Remote sensing</topic><topic>support identification</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Shen, Huanfeng</creatorcontrib><creatorcontrib>Du, Lijun</creatorcontrib><creatorcontrib>Zhang, Liangpei</creatorcontrib><creatorcontrib>Gong, Wei</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><jtitle>IEEE geoscience and remote sensing letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Shen, Huanfeng</au><au>Du, Lijun</au><au>Zhang, Liangpei</au><au>Gong, Wei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Blind Restoration Method for Remote Sensing Images</atitle><jtitle>IEEE geoscience and remote sensing letters</jtitle><stitle>LGRS</stitle><date>2012-11-01</date><risdate>2012</risdate><volume>9</volume><issue>6</issue><spage>1137</spage><epage>1141</epage><pages>1137-1141</pages><issn>1545-598X</issn><eissn>1558-0571</eissn><coden>IGRSBY</coden><abstract>This letter proposes a blind image restoration method for the deblurring of remote sensing images. A simple but robust identification method of point spread function (PSF) support is proposed, and a joint estimation method is presented to simultaneously solve the PSF coefficients and restoration image. To narrow the solution space for the best possible definition, the Huber-Markov (Huber-Markov random field) prior model is employed to regularize the two series of unknowns. Experiments were performed to demonstrate the effectiveness of the proposed approach.</abstract><pub>IEEE</pub><doi>10.1109/LGRS.2012.2190038</doi><tpages>5</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 1545-598X |
| ispartof | IEEE geoscience and remote sensing letters, 2012-11, Vol.9 (6), p.1137-1141 |
| issn | 1545-598X 1558-0571 |
| language | eng |
| recordid | cdi_ieee_primary_6194272 |
| source | IEEE Electronic Library (IEL) |
| subjects | Blind restoration Deconvolution Estimation Image restoration joint estimation Joints Measurement Optimized production technology Remote sensing support identification |
| title | A Blind Restoration Method for Remote Sensing Images |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-03T10%3A26%3A01IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-crossref_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20Blind%20Restoration%20Method%20for%20Remote%20Sensing%20Images&rft.jtitle=IEEE%20geoscience%20and%20remote%20sensing%20letters&rft.au=Shen,%20Huanfeng&rft.date=2012-11-01&rft.volume=9&rft.issue=6&rft.spage=1137&rft.epage=1141&rft.pages=1137-1141&rft.issn=1545-598X&rft.eissn=1558-0571&rft.coden=IGRSBY&rft_id=info:doi/10.1109/LGRS.2012.2190038&rft_dat=%3Ccrossref_RIE%3E10_1109_LGRS_2012_2190038%3C/crossref_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=6194272&rfr_iscdi=true |