Multispectral image restoration with multisensors
A procedure is advanced to restore a single color image, which has been degraded by a linear shift-invariant blur in the presence of additive noise. Four sensors are needed, followed by the application of the RGB-YIQ transformation. Subsequently, one 3-D Wiener filtration is required on a sequence o...
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| container_end_page | 998 vol.3 |
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| creator | Boo, K.J. Bose, N.K. |
| description | A procedure is advanced to restore a single color image, which has been degraded by a linear shift-invariant blur in the presence of additive noise. Four sensors are needed, followed by the application of the RGB-YIQ transformation. Subsequently, one 3-D Wiener filtration is required on a sequence of two luminance components and a 2-D Wiener filter is needed on each of the two chrominance components. For the procedure to be successful, the imposition of a strongly coprime condition on the wavenumber response of two distinct sensor blur functions is necessary. The resulting well-conditioned problem is shown to provide high-quality color images. |
| doi_str_mv | 10.1109/ICIP.1996.560993 |
| format | Conference Proceeding |
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Four sensors are needed, followed by the application of the RGB-YIQ transformation. Subsequently, one 3-D Wiener filtration is required on a sequence of two luminance components and a 2-D Wiener filter is needed on each of the two chrominance components. For the procedure to be successful, the imposition of a strongly coprime condition on the wavenumber response of two distinct sensor blur functions is necessary. The resulting well-conditioned problem is shown to provide high-quality color images.</description><identifier>ISBN: 9780780332591</identifier><identifier>ISBN: 0780332598</identifier><identifier>DOI: 10.1109/ICIP.1996.560993</identifier><language>eng</language><publisher>IEEE</publisher><subject>Additive noise ; Color ; Colored noise ; Degradation ; Image restoration ; Image sensors ; Layout ; Multispectral imaging ; Sensor phenomena and characterization ; Wiener filter</subject><ispartof>Proceedings of 3rd IEEE International Conference on Image Processing, 1996, Vol.3, p.995-998 vol.3</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/560993$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,4050,4051,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/560993$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Boo, K.J.</creatorcontrib><creatorcontrib>Bose, N.K.</creatorcontrib><title>Multispectral image restoration with multisensors</title><title>Proceedings of 3rd IEEE International Conference on Image Processing</title><addtitle>ICIP</addtitle><description>A procedure is advanced to restore a single color image, which has been degraded by a linear shift-invariant blur in the presence of additive noise. Four sensors are needed, followed by the application of the RGB-YIQ transformation. Subsequently, one 3-D Wiener filtration is required on a sequence of two luminance components and a 2-D Wiener filter is needed on each of the two chrominance components. For the procedure to be successful, the imposition of a strongly coprime condition on the wavenumber response of two distinct sensor blur functions is necessary. The resulting well-conditioned problem is shown to provide high-quality color images.</description><subject>Additive noise</subject><subject>Color</subject><subject>Colored noise</subject><subject>Degradation</subject><subject>Image restoration</subject><subject>Image sensors</subject><subject>Layout</subject><subject>Multispectral imaging</subject><subject>Sensor phenomena and characterization</subject><subject>Wiener filter</subject><isbn>9780780332591</isbn><isbn>0780332598</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>1996</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotT8tKxEAQHBBBWXMXT_mBxOl5JOmjBB-BFT3oeemd9OhIdrPMjIh_b3C3KKhLUQ8hrkHWABJvh354rQGxqW0jEfWZKLDt5EKtlUW4EEVKX3KBsVZ18lLA8_eUQzqwy5GmMuzog8vIKc-Rcpj35U_In-Xu38T7NMd0Jc49TYmLk67E-8P9W_9UrV8eh_5uXQWQJlfQUmuU965Fs5WMMIIyDhvvlm72QNxqPxrVOb3tDI5MmsjZUWkyjhrQK3FzzA3MvDnEZVr83Rx_6T8HaUQY</recordid><startdate>1996</startdate><enddate>1996</enddate><creator>Boo, K.J.</creator><creator>Bose, N.K.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>1996</creationdate><title>Multispectral image restoration with multisensors</title><author>Boo, K.J. ; Bose, N.K.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i104t-17a742ffc794b0e91d124c96fc045ef1ae73fd428c3b849dea3aac5d23a4ca613</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>1996</creationdate><topic>Additive noise</topic><topic>Color</topic><topic>Colored noise</topic><topic>Degradation</topic><topic>Image restoration</topic><topic>Image sensors</topic><topic>Layout</topic><topic>Multispectral imaging</topic><topic>Sensor phenomena and characterization</topic><topic>Wiener filter</topic><toplevel>online_resources</toplevel><creatorcontrib>Boo, K.J.</creatorcontrib><creatorcontrib>Bose, N.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 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>Boo, K.J.</au><au>Bose, N.K.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Multispectral image restoration with multisensors</atitle><btitle>Proceedings of 3rd IEEE International Conference on Image Processing</btitle><stitle>ICIP</stitle><date>1996</date><risdate>1996</risdate><volume>3</volume><spage>995</spage><epage>998 vol.3</epage><pages>995-998 vol.3</pages><isbn>9780780332591</isbn><isbn>0780332598</isbn><abstract>A procedure is advanced to restore a single color image, which has been degraded by a linear shift-invariant blur in the presence of additive noise. Four sensors are needed, followed by the application of the RGB-YIQ transformation. Subsequently, one 3-D Wiener filtration is required on a sequence of two luminance components and a 2-D Wiener filter is needed on each of the two chrominance components. For the procedure to be successful, the imposition of a strongly coprime condition on the wavenumber response of two distinct sensor blur functions is necessary. The resulting well-conditioned problem is shown to provide high-quality color images.</abstract><pub>IEEE</pub><doi>10.1109/ICIP.1996.560993</doi></addata></record> |
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| identifier | ISBN: 9780780332591 |
| ispartof | Proceedings of 3rd IEEE International Conference on Image Processing, 1996, Vol.3, p.995-998 vol.3 |
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| language | eng |
| recordid | cdi_ieee_primary_560993 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Additive noise Color Colored noise Degradation Image restoration Image sensors Layout Multispectral imaging Sensor phenomena and characterization Wiener filter |
| title | Multispectral image restoration with multisensors |
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