Multichannel image identification and restoration using continuousspatial domain modeling
In this paper, a novel identification technique for multichannel image processing is presented. Using the maximum likelihood estimation (ML) approach, the image is represented as an autoregressive (AR) model and blur is described as a continuous spatial domain model. Such a formulation overcomes som...
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| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , |
| التنسيق: | article |
| منشور في: |
1997
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://eprints.kfupm.edu.sa/id/eprint/14443/1/14443_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14443/2/14443_2.doc |
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| _version_ | 1864513384114814976 |
|---|---|
| author | Al-Suwailem, U.A. |
| author2 | Keller, J. unknown |
| author2_role | author author |
| author_facet | Al-Suwailem, U.A. Keller, J. unknown |
| author_role | author |
| dc.creator.none.fl_str_mv | Al-Suwailem, U.A. Keller, J. unknown |
| dc.date.none.fl_str_mv | 1997-10 2020 |
| dc.format.none.fl_str_mv | application/pdf application/msword |
| dc.identifier.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/14443/1/14443_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14443/2/14443_2.doc (1997) Multichannel image identification and restoration using continuousspatial domain modeling. Image Processing, 1997. Proceedings., International conference, 2. |
| dc.language.none.fl_str_mv | en en |
| dc.publisher.none.fl_str_mv | IEEE |
| dc.relation.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/14443/ |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Computer |
| dc.title.none.fl_str_mv | Multichannel image identification and restoration using continuousspatial domain modeling |
| dc.type.none.fl_str_mv | Article PeerReviewed info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | In this paper, a novel identification technique for multichannel image processing is presented. Using the maximum likelihood estimation (ML) approach, the image is represented as an autoregressive (AR) model and blur is described as a continuous spatial domain model. Such a formulation overcomes some major limitations encountered in other ML methods. Moreover, cross-spectral and spatial components are incorporated in the multichannel modeling. It is shown that by incorporating those components, the overall performance is improved significantly. Also, experimental results show that blur extent can be optimally identified from noisy color images that are degraded by uniform linear motion or out-of-focus blurs |
| eu_rights_str_mv | openAccess |
| format | article |
| id | KFUPM_89061a66e3346bdfdd05b0c61c9a1a42 |
| identifier_str_mv | (1997) Multichannel image identification and restoration using continuousspatial domain modeling. Image Processing, 1997. Proceedings., International conference, 2. |
| language_invalid_str_mv | en |
| network_acronym_str | KFUPM |
| network_name_str | King Fahd University of Petroleum and Minerals |
| oai_identifier_str | oai::14443 |
| publishDate | 1997 |
| publisher.none.fl_str_mv | IEEE |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Multichannel image identification and restoration using continuousspatial domain modelingAl-Suwailem, U.A.Keller, J.unknownComputerIn this paper, a novel identification technique for multichannel image processing is presented. Using the maximum likelihood estimation (ML) approach, the image is represented as an autoregressive (AR) model and blur is described as a continuous spatial domain model. Such a formulation overcomes some major limitations encountered in other ML methods. Moreover, cross-spectral and spatial components are incorporated in the multichannel modeling. It is shown that by incorporating those components, the overall performance is improved significantly. Also, experimental results show that blur extent can be optimally identified from noisy color images that are degraded by uniform linear motion or out-of-focus blursIEEE1997-102020ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/mswordhttps://eprints.kfupm.edu.sa/id/eprint/14443/1/14443_1.pdfhttps://eprints.kfupm.edu.sa/id/eprint/14443/2/14443_2.doc (1997) Multichannel image identification and restoration using continuousspatial domain modeling. Image Processing, 1997. Proceedings., International conference, 2. enenhttps://eprints.kfupm.edu.sa/id/eprint/14443/info:eu-repo/semantics/openAccessoai::144432019-11-01T14:05:50Z |
| spellingShingle | Multichannel image identification and restoration using continuousspatial domain modeling Al-Suwailem, U.A. Computer |
| status_str | publishedVersion |
| title | Multichannel image identification and restoration using continuousspatial domain modeling |
| title_full | Multichannel image identification and restoration using continuousspatial domain modeling |
| title_fullStr | Multichannel image identification and restoration using continuousspatial domain modeling |
| title_full_unstemmed | Multichannel image identification and restoration using continuousspatial domain modeling |
| title_short | Multichannel image identification and restoration using continuousspatial domain modeling |
| title_sort | Multichannel image identification and restoration using continuousspatial domain modeling |
| topic | Computer |
| url | https://eprints.kfupm.edu.sa/id/eprint/14443/1/14443_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14443/2/14443_2.doc |