{"created":"2023-05-15T15:32:25.039027+00:00","id":5331,"links":{},"metadata":{"_buckets":{"deposit":"cd45cb8b-b5b7-4017-954e-2cf18bdfef7c"},"_deposit":{"created_by":17,"id":"5331","owners":[17],"pid":{"revision_id":0,"type":"depid","value":"5331"},"status":"published"},"_oai":{"id":"oai:barrel.repo.nii.ac.jp:00005331","sets":["1:647"]},"author_link":["32809","32808"],"item_1_biblio_info_5":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2019","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicPageEnd":"280","bibliographicPageStart":"267","bibliographicVolumeNumber":"13","bibliographic_titles":[{},{"bibliographic_title":"The Review of Socionetwork Strategies","bibliographic_titleLang":"en"}]}]},"item_1_description_18":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"In this paper, we propose a fast image denoising method based on discrete Markov random fields and the fast Fourier transform. The purpose of the image denoising is to infer the original noiseless image from a noise corrupted image. We consider the case where several noisy images are available for inferring the original image and the Bayesian approach is adopted to create the posterior probability distribution of the denoised image. In the proposed method, the estimation of the denoised image is achieved using belief propagation and an expectation-maximization algorithm. We numerically verified the performance of the proposed method using several standard images.","subitem_description_type":"Abstract"}]},"item_1_full_name_3":{"attribute_name":"著者別名","attribute_value_mlt":[{"nameIdentifiers":[{"nameIdentifier":"32808","nameIdentifierScheme":"WEKO"}],"names":[{"name":"片岡, 駿"}]}]},"item_1_publisher_6":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Springer"}]},"item_1_relation_8":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_type":"isIdenticalTo","subitem_relation_type_id":{"subitem_relation_type_id_text":"10.1007/s12626-019-00043-3","subitem_relation_type_select":"DOI"}}]},"item_1_rights_12":{"attribute_name":"権利表記","attribute_value_mlt":[{"subitem_rights":"© The Author(s) 2019"}]},"item_1_rights_13":{"attribute_name":"出版社版URI","attribute_value_mlt":[{"subitem_rights":"https://link.springer.com/article/10.1007/s12626-019-00043-3"}]},"item_1_source_id_7":{"attribute_name":"ISSN / EISSN","attribute_value_mlt":[{"subitem_source_identifier":"2523-3173","subitem_source_identifier_type":"ISSN"}]},"item_1_subject_16":{"attribute_name":"日本十進分類法","attribute_value_mlt":[{"subitem_subject":"410","subitem_subject_scheme":"NDC"}]},"item_1_subject_17":{"attribute_name":"NIIサブジェクト","attribute_value_mlt":[{"subitem_subject":"数学","subitem_subject_scheme":"Other"}]},"item_1_version_type_15":{"attribute_name":"テキストバージョン","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Kataoka, Shun"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yasuda, Muneki"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2019-11-22"}],"displaytype":"detail","filename":"TheReviewofSocionetworkStrategies-13.pdf","filesize":[{"value":"1.6 MB"}],"format":"application/pdf","licensetype":"license_6","mimetype":"application/pdf","url":{"label":"TheReviewofSocionetworkStrategies-13","url":"https://barrel.repo.nii.ac.jp/record/5331/files/TheReviewofSocionetworkStrategies-13.pdf"},"version_id":"15b3adf1-ad21-427d-9763-d83884fbd6e8"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Image denoising","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Discrete Markov random field","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Belief propagation","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"EM algorithm","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"FFT","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"Bayesian Image Denoising with Multiple Noisy Images","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Bayesian Image Denoising with Multiple Noisy Images"}]},"item_type_id":"1","owner":"17","path":["647"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-11-22"},"publish_date":"2019-11-22","publish_status":"0","recid":"5331","relation_version_is_last":true,"title":["Bayesian Image Denoising with Multiple Noisy Images"],"weko_creator_id":"17","weko_shared_id":-1},"updated":"2023-05-15T16:02:06.984758+00:00"}