A Semidiscrete Version of the Citti-Petitot-Sarti Model as a Plausible Model for Anthropomorphic Image Reconstruction and Pattern Recognition

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Special Collection:e-book
Format: Book
Language:English
Published: Cham : : Springer International Publishing : Imprint: Springer,, 2018
Edition:1st ed. 2018.
Series:SpringerBriefs in Mathematics,, ISSN 2191-8198
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Online Access:https://doi.org/10.1007/978-3-319-78482-3
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id opac-EUL01-000979532
collection e-book
institution L_200
EUL01
spelling Prandi, Dario. szerző aut http://id.loc.gov/vocabulary/relators/aut
A Semidiscrete Version of the Citti-Petitot-Sarti Model as a Plausible Model for Anthropomorphic Image Reconstruction and Pattern Recognition by Dario Prandi, Jean-Paul Gauthier.
1st ed. 2018.
Cham : Springer International Publishing : Imprint: Springer, 2018
XIV, 113 p. 14 illus., 6 illus. in color. online forrás
szöveg txt rdacontent
számítógépes c rdamedia
távoli hozzáférés cr rdacarrier
szövegfájl PDF rda
SpringerBriefs in Mathematics, 2191-8198
1 Introduction -- 2 Preliminaries -- 3 Lifts -- 4 Almost-periodic interpolation and approximation -- 5 Pattern recognition -- 6 Image reconstruction -- 7 Applications -- 8 Appendix: A Circulant matrices -- 9 Appendix B: Bispectrally admissible sets.
This book proposes a semi-discrete version of the theory of Petitot and Citti-Sarti, leading to a left-invariant structure over the group SE(2,N), restricted to a finite number of rotations. This apparently very simple group is in fact quite atypical: it is maximally almost periodic, which leads to much simpler harmonic analysis compared to SE(2). Based upon this semi-discrete model, the authors improve on previous image-reconstruction algorithms and develop a pattern-recognition theory that also leads to very efficient algorithms in practice.
Nyomtatott kiadás: ISBN 9783319784816
Nyomtatott kiadás: ISBN 9783319784830
Az e-könyvek a teljes ELTE IP-tartományon belül online elérhetők.
könyv
e-book
Harmonic analysis. EUL10000275880 Y
Computer vision. EUL10000467498 Y
Abstract Harmonic Analysis.
Mathematical Applications in Computer Science.
Computer Imaging, Vision, Pattern Recognition and Graphics.
elektronikus könyv
Gauthier, Jean-Paul. szerző aut http://id.loc.gov/vocabulary/relators/aut
SpringerLink (Online service) közreadó testület
Online változat https://doi.org/10.1007/978-3-319-78482-3
EUL01
language English
format Book
author Prandi, Dario., szerző
spellingShingle Prandi, Dario., szerző
A Semidiscrete Version of the Citti-Petitot-Sarti Model as a Plausible Model for Anthropomorphic Image Reconstruction and Pattern Recognition
SpringerBriefs in Mathematics,, ISSN 2191-8198
Harmonic analysis.
Computer vision.
Abstract Harmonic Analysis.
Mathematical Applications in Computer Science.
Computer Imaging, Vision, Pattern Recognition and Graphics.
elektronikus könyv
author_facet Prandi, Dario., szerző
Gauthier, Jean-Paul., szerző
SpringerLink (Online service)
author2 Gauthier, Jean-Paul., szerző
author_corporate SpringerLink (Online service)
author_sort Prandi, Dario.
title A Semidiscrete Version of the Citti-Petitot-Sarti Model as a Plausible Model for Anthropomorphic Image Reconstruction and Pattern Recognition
title_short A Semidiscrete Version of the Citti-Petitot-Sarti Model as a Plausible Model for Anthropomorphic Image Reconstruction and Pattern Recognition
title_full A Semidiscrete Version of the Citti-Petitot-Sarti Model as a Plausible Model for Anthropomorphic Image Reconstruction and Pattern Recognition by Dario Prandi, Jean-Paul Gauthier.
title_fullStr A Semidiscrete Version of the Citti-Petitot-Sarti Model as a Plausible Model for Anthropomorphic Image Reconstruction and Pattern Recognition by Dario Prandi, Jean-Paul Gauthier.
title_full_unstemmed A Semidiscrete Version of the Citti-Petitot-Sarti Model as a Plausible Model for Anthropomorphic Image Reconstruction and Pattern Recognition by Dario Prandi, Jean-Paul Gauthier.
title_auth A Semidiscrete Version of the Citti-Petitot-Sarti Model as a Plausible Model for Anthropomorphic Image Reconstruction and Pattern Recognition
title_sort semidiscrete version of the citti petitot sarti model as a plausible model for anthropomorphic image reconstruction and pattern recognition
series SpringerBriefs in Mathematics,, ISSN 2191-8198
series2 SpringerBriefs in Mathematics,
publishDate 2018
publishDateSort 2018
physical XIV, 113 p. 14 illus., 6 illus. in color. : online forrás
edition 1st ed. 2018.
isbn 978-3-319-78482-3
issn 2191-8198
callnumber-first Q - Science
callnumber-subject QA - Mathematics
callnumber-label QA403-403
callnumber-raw 979532
callnumber-search 979532
topic Harmonic analysis.
Computer vision.
Abstract Harmonic Analysis.
Mathematical Applications in Computer Science.
Computer Imaging, Vision, Pattern Recognition and Graphics.
elektronikus könyv
topic_facet Harmonic analysis.
Computer vision.
Abstract Harmonic Analysis.
Mathematical Applications in Computer Science.
Computer Imaging, Vision, Pattern Recognition and Graphics.
elektronikus könyv
Harmonic analysis.
Computer vision.
Abstract Harmonic Analysis.
Mathematical Applications in Computer Science.
Computer Imaging, Vision, Pattern Recognition and Graphics.
url https://doi.org/10.1007/978-3-319-78482-3
illustrated Not Illustrated
dewey-hundreds 500 - Science
dewey-tens 510 - Mathematics
dewey-ones 515 - Analysis
dewey-full 515.785
dewey-sort 3515.785
dewey-raw 515.785
dewey-search 515.785
first_indexed 2022-02-02T07:35:45Z
last_indexed 2022-03-11T06:51:11Z
recordtype opac
publisher Cham : : Springer International Publishing : Imprint: Springer,
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score 13,333448
generalnotes This book proposes a semi-discrete version of the theory of Petitot and Citti-Sarti, leading to a left-invariant structure over the group SE(2,N), restricted to a finite number of rotations. This apparently very simple group is in fact quite atypical: it is maximally almost periodic, which leads to much simpler harmonic analysis compared to SE(2). Based upon this semi-discrete model, the authors improve on previous image-reconstruction algorithms and develop a pattern-recognition theory that also leads to very efficient algorithms in practice.