Compressive imaging: structure, sampling, learning
Accurate, robust and fast image reconstruction is a critical task in many scientific, industrial and medical applications. Over the last decade, image reconstruction has been revolutionized by the rise of compressive imaging. It has fundamentally changed the way modern image reconstruction is perfor...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2021
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| Schlagworte: | |
| Zusammenfassung: | Accurate, robust and fast image reconstruction is a critical task in many scientific, industrial and medical applications. Over the last decade, image reconstruction has been revolutionized by the rise of compressive imaging. It has fundamentally changed the way modern image reconstruction is performed. This in-depth treatment of the subject commences with a practical introduction to compressive imaging, supplemented with examples and downloadable code, intended for readers without extensive background in the subject. Next, it introduces core topics in compressive imaging - including compressed sensing, wavelets and optimization - in a concise yet rigorous way, before providing a detailed treatment of the mathematics of compressive imaging. The final part is devoted to recent trends in compressive imaging: deep learning and neural networks. With an eye to the next decade of imaging research, and using both empirical and mathematical insights, it examines the potential benefits and the pitfalls of these latest approaches |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 16 Jul 2021) |
| Beschreibung: | xv, 601 Seiten Illustrationen, Diagramme |
| ISBN: | 9781108421614 |
Internformat
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Datensatz im Suchindex
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| author | Adcock, Ben ca. 20./21. Jh Hansen, Anders ca. 20./21. Jh |
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| dewey-full | 006.6 |
| dewey-hundreds | 000 - Computer science, information, general works |
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| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik Mathematik |
| discipline_str_mv | Informatik Mathematik |
| format | Book |
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| id | DE-604.BV047515881 |
| illustrated | Illustrated |
| index_date | 2024-07-03T18:23:08Z |
| indexdate | 2024-07-10T09:14:13Z |
| institution | BVB |
| isbn | 9781108421614 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032916651 |
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| physical | xv, 601 Seiten Illustrationen, Diagramme |
| publishDate | 2021 |
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| spelling | Adcock, Ben ca. 20./21. Jh. (DE-588)1240314817 aut Compressive imaging structure, sampling, learning Ben Adcock (Simon Fraser University), Anders C. Hansen (University of Cambridge) ; with contributions by Vegard Antun Cambridge Cambridge University Press 2021 xv, 601 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Title from publisher's bibliographic system (viewed on 16 Jul 2021) Accurate, robust and fast image reconstruction is a critical task in many scientific, industrial and medical applications. Over the last decade, image reconstruction has been revolutionized by the rise of compressive imaging. It has fundamentally changed the way modern image reconstruction is performed. This in-depth treatment of the subject commences with a practical introduction to compressive imaging, supplemented with examples and downloadable code, intended for readers without extensive background in the subject. Next, it introduces core topics in compressive imaging - including compressed sensing, wavelets and optimization - in a concise yet rigorous way, before providing a detailed treatment of the mathematics of compressive imaging. The final part is devoted to recent trends in compressive imaging: deep learning and neural networks. With an eye to the next decade of imaging research, and using both empirical and mathematical insights, it examines the potential benefits and the pitfalls of these latest approaches Image compression Digital images / Deconvolution Bildverarbeitung (DE-588)4006684-8 gnd rswk-swf Entfaltung Mathematik (DE-588)4014854-3 gnd rswk-swf Datenkompression (DE-588)4121121-2 gnd rswk-swf Bildverarbeitung (DE-588)4006684-8 s Datenkompression (DE-588)4121121-2 s Entfaltung Mathematik (DE-588)4014854-3 s DE-604 Hansen, Anders ca. 20./21. Jh. (DE-588)171675878 aut Erscheint auch als Online-Ausgabe 978-1-108-37744-7 |
| spellingShingle | Adcock, Ben ca. 20./21. Jh Hansen, Anders ca. 20./21. Jh Compressive imaging structure, sampling, learning Image compression Digital images / Deconvolution Bildverarbeitung (DE-588)4006684-8 gnd Entfaltung Mathematik (DE-588)4014854-3 gnd Datenkompression (DE-588)4121121-2 gnd |
| subject_GND | (DE-588)4006684-8 (DE-588)4014854-3 (DE-588)4121121-2 |
| title | Compressive imaging structure, sampling, learning |
| title_auth | Compressive imaging structure, sampling, learning |
| title_exact_search | Compressive imaging structure, sampling, learning |
| title_exact_search_txtP | Compressive imaging structure, sampling, learning |
| title_full | Compressive imaging structure, sampling, learning Ben Adcock (Simon Fraser University), Anders C. Hansen (University of Cambridge) ; with contributions by Vegard Antun |
| title_fullStr | Compressive imaging structure, sampling, learning Ben Adcock (Simon Fraser University), Anders C. Hansen (University of Cambridge) ; with contributions by Vegard Antun |
| title_full_unstemmed | Compressive imaging structure, sampling, learning Ben Adcock (Simon Fraser University), Anders C. Hansen (University of Cambridge) ; with contributions by Vegard Antun |
| title_short | Compressive imaging |
| title_sort | compressive imaging structure sampling learning |
| title_sub | structure, sampling, learning |
| topic | Image compression Digital images / Deconvolution Bildverarbeitung (DE-588)4006684-8 gnd Entfaltung Mathematik (DE-588)4014854-3 gnd Datenkompression (DE-588)4121121-2 gnd |
| topic_facet | Image compression Digital images / Deconvolution Bildverarbeitung Entfaltung Mathematik Datenkompression |
| work_keys_str_mv | AT adcockben compressiveimagingstructuresamplinglearning AT hansenanders compressiveimagingstructuresamplinglearning |