Markov Random Fields for Vision and Image Processing
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| Title: | Markov Random Fields for Vision and Image Processing |
|---|---|
| Description: | State-of-the-art research on MRFs, successful MRF applications, and advanced topics for future study.This volume demonstrates the power of the Markov random field (MRF) in vision, treating the MRF both as a tool for modeling image data and, utilizing recently developed algorithms, as a means of making inferences about images. These inferences concern underlying image and scene structure as well as solutions to such problems as image reconstruction, image segmentation, 3D vision, and object labeling. It offers key findings and state-of-the-art research on both algorithms and applications.After an introduction to the fundamental concepts used in MRFs, the book reviews some of the main algorithms for performing inference with MRFs; presents successful applications of MRFs, including segmentation, super-resolution, and image restoration, along with a comparison of various optimization methods; discusses advanced algorithmic topics; addresses limitations of the strong locality assumptions in the MRFs discussed in earlier chapters; and showcases applications that use MRFs in more complex ways, as components in bigger systems or with multiterm energy functions. The book will be an essential guide to current research on these powerful mathematical tools. |
| Authors: | Andrew Blake, Pushmeet Kohli, Carsten Rother |
| Resource Type: | eBook. |
| Subjects: | Markov random fields, Computer vision--Mathematics, Image processing--Mathematics, Computer graphics--Mathematics |
| Categories: | COMPUTERS / Image Processing |
| Database: | eBook Collection (EBSCOhost) |
| FullText | Links: – Type: ebook-pdf Text: Availability: 0 |
|---|---|
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| Items | – Name: Title Label: Title Group: Ti Data: Markov Random Fields for Vision and Image Processing – Name: Abstract Label: Description Group: Ab Data: State-of-the-art research on MRFs, successful MRF applications, and advanced topics for future study.This volume demonstrates the power of the Markov random field (MRF) in vision, treating the MRF both as a tool for modeling image data and, utilizing recently developed algorithms, as a means of making inferences about images. These inferences concern underlying image and scene structure as well as solutions to such problems as image reconstruction, image segmentation, 3D vision, and object labeling. It offers key findings and state-of-the-art research on both algorithms and applications.After an introduction to the fundamental concepts used in MRFs, the book reviews some of the main algorithms for performing inference with MRFs; presents successful applications of MRFs, including segmentation, super-resolution, and image restoration, along with a comparison of various optimization methods; discusses advanced algorithmic topics; addresses limitations of the strong locality assumptions in the MRFs discussed in earlier chapters; and showcases applications that use MRFs in more complex ways, as components in bigger systems or with multiterm energy functions. The book will be an essential guide to current research on these powerful mathematical tools. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Andrew+Blake%22">Andrew Blake</searchLink><br /><searchLink fieldCode="AR" term="%22Pushmeet+Kohli%22">Pushmeet Kohli</searchLink><br /><searchLink fieldCode="AR" term="%22Carsten+Rother%22">Carsten Rother</searchLink> – Name: TypePub Label: Resource Type Group: TypPub Data: eBook. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Markov+random+fields%22">Markov random fields</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+vision--Mathematics%22">Computer vision--Mathematics</searchLink><br /><searchLink fieldCode="DE" term="%22Image+processing--Mathematics%22">Image processing--Mathematics</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+graphics--Mathematics%22">Computer graphics--Mathematics</searchLink> – Name: SubjectBISAC Label: Categories Group: Su Data: <searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Image+Processing%22">COMPUTERS / Image Processing</searchLink> |
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| RecordInfo | BibRecord: BibEntity: Classifications: – Code: 006.370151 Scheme: ddc Type: prePub Languages: – Code: eng Text: English Subjects: – SubjectFull: Markov random fields Type: general – SubjectFull: Computer vision--Mathematics Type: general – SubjectFull: Image processing--Mathematics Type: general – SubjectFull: Computer graphics--Mathematics Type: general Titles: – TitleFull: Markov Random Fields for Vision and Image Processing Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Andrew Blake – PersonEntity: Name: NameFull: Pushmeet Kohli – PersonEntity: Name: NameFull: Carsten Rother – PersonEntity: Name: NameFull: Andrew Blake – PersonEntity: Name: NameFull: Pushmeet Kohli – PersonEntity: Name: NameFull: Carsten Rother IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2011 – D: 04 M: 02 Type: profile Y: 2014 Identifiers: – Type: isbn-print Value: 9780262015776 – Type: isbn-electronic Value: 9780262298353 Titles: – TitleFull: Markov Random Fields for Vision and Image Processing Type: main |
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