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Record Nr. |
UNINA9910739437803321 |
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Autore |
Patel Vishal M |
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Titolo |
Sparse representations and compressive sensing for imaging and vision / / Vishal M. Patel, Rama Chellappa |
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Pubbl/distr/stampa |
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New York, : Springer, 2013 |
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ISBN |
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1-299-33549-7 |
1-4614-6381-5 |
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Edizione |
[1st ed. 2013.] |
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Descrizione fisica |
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1 online resource (x, 102 pages) : illustrations (some color) |
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Collana |
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SpringerBriefs in electrical and computer engineering |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Imaging |
Signal processing - Mathematics |
Vision |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Introduction -- Compressive Sensing -- Compressive Acquisition -- Compressive Sensing for Vision -- Sparse Representation-based Object Recognition -- Dictionary Learning -- Concluding Remarks. |
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Sommario/riassunto |
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Compressed sensing or compressive sensing is a new concept in signal processing where one measures a small number of non-adaptive linear combinations of the signal. These measurements are usually much smaller than the number of samples that define the signal. From these small numbers of measurements, the signal is then reconstructed by non-linear procedure. Compressed sensing has recently emerged as a powerful tool for efficiently processing data in non-traditional ways. In this book, we highlight some of the key mathematical insights underlying sparse representation and compressed sensing and illustrate the role of these theories in classical vision, imaging and biometrics problems. |
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