Sparse image and signal processing: wavelets, curvelets, morphological diversity
This book presents the state of the art in sparse and multiscale image and signal processing, covering linear multiscale transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Recent concepts of s...
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2010
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| Schlagworte: | |
| Online-Zugang: | BSB01 FHN01 Volltext |
| Zusammenfassung: | This book presents the state of the art in sparse and multiscale image and signal processing, covering linear multiscale transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Recent concepts of sparsity and morphological diversity are described and exploited for various problems such as denoising, inverse problem regularization, sparse signal decomposition, blind source separation, and compressed sensing. This book weds theory and practice in examining applications in areas such as astronomy, biology, physics, digital media, and forensics. A final chapter explores a paradigm shift in signal processing, showing that previous limits to information sampling and extraction can be overcome in very significant ways. Matlab and IDL code accompany these methods and applications to reproduce the experiments and illustrate the reasoning and methodology of the research are available for download at the associated web site |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 05 Oct 2015) |
| Beschreibung: | 1 online resource (xvii, 316 pages) |
| ISBN: | 9780511730344 |
| DOI: | 10.1017/CBO9780511730344 |
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| 505 | 8 | |a Introduction to the world of sparsity -- The wavelet transform -- Redundant wavelet transform -- Nonlinear multiscale transforms -- The ridgelet and curvelet transforms -- Sparsity and noise removal -- Linear inverse problems -- Morphological diversity -- Sparse blind source separation -- Multiscale geometric analysis on the sphere -- Compressed sensing | |
| 520 | |a This book presents the state of the art in sparse and multiscale image and signal processing, covering linear multiscale transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Recent concepts of sparsity and morphological diversity are described and exploited for various problems such as denoising, inverse problem regularization, sparse signal decomposition, blind source separation, and compressed sensing. This book weds theory and practice in examining applications in areas such as astronomy, biology, physics, digital media, and forensics. A final chapter explores a paradigm shift in signal processing, showing that previous limits to information sampling and extraction can be overcome in very significant ways. Matlab and IDL code accompany these methods and applications to reproduce the experiments and illustrate the reasoning and methodology of the research are available for download at the associated web site | ||
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| 650 | 4 | |a Sparse matrices | |
| 650 | 4 | |a Wavelets (Mathematics) | |
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Datensatz im Suchindex
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| author | Starck, J.-L 1965- |
| author_facet | Starck, J.-L 1965- |
| author_role | aut |
| author_sort | Starck, J.-L 1965- |
| author_variant | j l s jls |
| building | Verbundindex |
| bvnumber | BV043943886 |
| classification_rvk | ZN 6040 |
| collection | ZDB-20-CBO |
| contents | Introduction to the world of sparsity -- The wavelet transform -- Redundant wavelet transform -- Nonlinear multiscale transforms -- The ridgelet and curvelet transforms -- Sparsity and noise removal -- Linear inverse problems -- Morphological diversity -- Sparse blind source separation -- Multiscale geometric analysis on the sphere -- Compressed sensing |
| ctrlnum | (ZDB-20-CBO)CR9780511730344 (OCoLC)852524601 (DE-599)BVBBV043943886 |
| dewey-full | 621.36/7 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 621 - Applied physics |
| dewey-raw | 621.36/7 |
| dewey-search | 621.36/7 |
| dewey-sort | 3621.36 17 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Elektrotechnik / Elektronik / Nachrichtentechnik |
| doi_str_mv | 10.1017/CBO9780511730344 |
| format | Electronic eBook |
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| id | DE-604.BV043943886 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:39:20Z |
| institution | BVB |
| isbn | 9780511730344 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029352857 |
| oclc_num | 852524601 |
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| owner_facet | DE-12 DE-92 |
| physical | 1 online resource (xvii, 316 pages) |
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| publishDate | 2010 |
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| publisher | Cambridge University Press |
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| spelling | Starck, J.-L 1965- Verfasser aut Sparse image and signal processing wavelets, curvelets, morphological diversity Jean-Luc Starck, Fionn Murtagh, Jalal M. Fadili Sparse Image & Signal Processing Cambridge Cambridge University Press 2010 1 online resource (xvii, 316 pages) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 05 Oct 2015) Introduction to the world of sparsity -- The wavelet transform -- Redundant wavelet transform -- Nonlinear multiscale transforms -- The ridgelet and curvelet transforms -- Sparsity and noise removal -- Linear inverse problems -- Morphological diversity -- Sparse blind source separation -- Multiscale geometric analysis on the sphere -- Compressed sensing This book presents the state of the art in sparse and multiscale image and signal processing, covering linear multiscale transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Recent concepts of sparsity and morphological diversity are described and exploited for various problems such as denoising, inverse problem regularization, sparse signal decomposition, blind source separation, and compressed sensing. This book weds theory and practice in examining applications in areas such as astronomy, biology, physics, digital media, and forensics. A final chapter explores a paradigm shift in signal processing, showing that previous limits to information sampling and extraction can be overcome in very significant ways. Matlab and IDL code accompany these methods and applications to reproduce the experiments and illustrate the reasoning and methodology of the research are available for download at the associated web site Transformations (Mathematics) Signal processing Image processing Sparse matrices Wavelets (Mathematics) Compressed sensing (Telecommunication) Nachrichtenübertragungstechnik (DE-588)4139364-8 gnd rswk-swf Wavelet (DE-588)4215427-3 gnd rswk-swf Bildübertragung (DE-588)4145457-1 gnd rswk-swf Nachrichtenübertragungstechnik (DE-588)4139364-8 s Bildübertragung (DE-588)4145457-1 s Wavelet (DE-588)4215427-3 s 1\p DE-604 Murtagh, Fionn Sonstige oth Fadili, Jalal M. 1973- Sonstige oth Erscheint auch als Druckausgabe 978-0-521-11913-9 https://doi.org/10.1017/CBO9780511730344 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Starck, J.-L 1965- Sparse image and signal processing wavelets, curvelets, morphological diversity Introduction to the world of sparsity -- The wavelet transform -- Redundant wavelet transform -- Nonlinear multiscale transforms -- The ridgelet and curvelet transforms -- Sparsity and noise removal -- Linear inverse problems -- Morphological diversity -- Sparse blind source separation -- Multiscale geometric analysis on the sphere -- Compressed sensing Transformations (Mathematics) Signal processing Image processing Sparse matrices Wavelets (Mathematics) Compressed sensing (Telecommunication) Nachrichtenübertragungstechnik (DE-588)4139364-8 gnd Wavelet (DE-588)4215427-3 gnd Bildübertragung (DE-588)4145457-1 gnd |
| subject_GND | (DE-588)4139364-8 (DE-588)4215427-3 (DE-588)4145457-1 |
| title | Sparse image and signal processing wavelets, curvelets, morphological diversity |
| title_alt | Sparse Image & Signal Processing |
| title_auth | Sparse image and signal processing wavelets, curvelets, morphological diversity |
| title_exact_search | Sparse image and signal processing wavelets, curvelets, morphological diversity |
| title_full | Sparse image and signal processing wavelets, curvelets, morphological diversity Jean-Luc Starck, Fionn Murtagh, Jalal M. Fadili |
| title_fullStr | Sparse image and signal processing wavelets, curvelets, morphological diversity Jean-Luc Starck, Fionn Murtagh, Jalal M. Fadili |
| title_full_unstemmed | Sparse image and signal processing wavelets, curvelets, morphological diversity Jean-Luc Starck, Fionn Murtagh, Jalal M. Fadili |
| title_short | Sparse image and signal processing |
| title_sort | sparse image and signal processing wavelets curvelets morphological diversity |
| title_sub | wavelets, curvelets, morphological diversity |
| topic | Transformations (Mathematics) Signal processing Image processing Sparse matrices Wavelets (Mathematics) Compressed sensing (Telecommunication) Nachrichtenübertragungstechnik (DE-588)4139364-8 gnd Wavelet (DE-588)4215427-3 gnd Bildübertragung (DE-588)4145457-1 gnd |
| topic_facet | Transformations (Mathematics) Signal processing Image processing Sparse matrices Wavelets (Mathematics) Compressed sensing (Telecommunication) Nachrichtenübertragungstechnik Wavelet Bildübertragung |
| url | https://doi.org/10.1017/CBO9780511730344 |
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