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DC Field | Value | Language |
---|---|---|
dc.citation.number | 6 | - |
dc.citation.startPage | 201 | - |
dc.citation.title | ACM TRANSACTIONS ON GRAPHICS | - |
dc.citation.volume | 32 | - |
dc.contributor.author | Granados, Miguel | - |
dc.contributor.author | Kim, Kwang In | - |
dc.contributor.author | Tompkin, James | - |
dc.contributor.author | Theobalt, Christian | - |
dc.date.accessioned | 2023-12-22T03:12:59Z | - |
dc.date.available | 2023-12-22T03:12:59Z | - |
dc.date.created | 2019-02-25 | - |
dc.date.issued | 2013-11 | - |
dc.description.abstract | High dynamic range reconstruction of dynamic scenes requires careful handling of dynamic objects to prevent ghosting. However, in a recent review, Srikantha et al. [2012] conclude that "there is no single best method and the selection of an approach depends on the user's goal". We attempt to solve this problem with a novel approach that models the noise distribution of color values. We estimate the likelihood that a pair of colors in different images are observations of the same irradiance, and we use a Markov random field prior to reconstruct irradiance from pixels that are likely to correspond to the same static scene object. Dynamic content is handled by selecting a single low dynamic range source image and hand-held capture is supported through homography-based image alignment. Our noise-based reconstruction method achieves better ghost detection and removal than state-of-the-art methods for cluttered scenes with large object displacements. As such, our method is broadly applicable and helps move the field towards a single method for dynamic scene HDR reconstruction. | - |
dc.identifier.bibliographicCitation | ACM TRANSACTIONS ON GRAPHICS, v.32, no.6, pp.201 | - |
dc.identifier.doi | 10.1145/2508363.2508410 | - |
dc.identifier.issn | 0730-0301 | - |
dc.identifier.scopusid | 2-s2.0-84887849546 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/26251 | - |
dc.identifier.url | https://dl.acm.org/citation.cfm?doid=2508363.2508410 | - |
dc.identifier.wosid | 000326923200045 | - |
dc.language | 영어 | - |
dc.publisher | ASSOC COMPUTING MACHINERY | - |
dc.title | Automatic Noise Modeling for Ghost-free HDR Reconstruction | - |
dc.type | Article | - |
dc.description.isOpenAccess | FALSE | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Software Engineering | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.type.docType | Article; Proceedings Paper | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | HDR deghosting | - |
dc.subject.keywordAuthor | camera noise | - |
dc.subject.keywordAuthor | motion detection | - |
dc.subject.keywordPlus | DYNAMIC SCENES | - |
dc.subject.keywordPlus | IMAGE | - |
dc.subject.keywordPlus | ENHANCEMENT | - |
dc.subject.keywordPlus | REMOVAL | - |
dc.subject.keywordPlus | VIDEO | - |
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