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Sparse Representations and Compressive Sensing for Imaging and Vision
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 measuremen...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York, NY :
Springer New York : Imprint: Springer,
2013.
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| Edición: | 1st ed. 2013. |
| Colección: | SpringerBriefs in Electrical and Computer Engineering,
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| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 100 | 1 | |a Patel, Vishal M. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Sparse Representations and Compressive Sensing for Imaging and Vision |h [electronic resource] / |c by Vishal M. Patel, Rama Chellappa. |
| 250 | |a 1st ed. 2013. | ||
| 264 | 1 | |a New York, NY : |b Springer New York : |b Imprint: Springer, |c 2013. | |
| 300 | |a X, 102 p. 41 illus. |b online resource. | ||
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| 490 | 1 | |a SpringerBriefs in Electrical and Computer Engineering, |x 2191-8120 | |
| 505 | 0 | |a Introduction -- Compressive Sensing -- Compressive Acquisition -- Compressive Sensing for Vision -- Sparse Representation-based Object Recognition -- Dictionary Learning -- Concluding Remarks. | |
| 520 | |a 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. | ||
| 650 | 0 | |a Signal processing. | |
| 650 | 0 | |a Computer vision. | |
| 650 | 1 | 4 | |a Signal, Speech and Image Processing . |
| 650 | 2 | 4 | |a Computer Vision. |
| 700 | 1 | |a Chellappa, Rama. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
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| 776 | 0 | 8 | |i Printed edition: |z 9781461463801 |
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| 830 | 0 | |a SpringerBriefs in Electrical and Computer Engineering, |x 2191-8120 | |
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| 950 | |a Engineering (SpringerNature-11647) | ||
| 950 | |a Engineering (R0) (SpringerNature-43712) | ||