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130220s2013 xxu| s |||| 0|eng d |
| 020 |
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|a 9781461463818
|9 978-1-4614-6381-8
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|a 10.1007/978-1-4614-6381-8
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|a 621.382
|2 23
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| 100 |
1 |
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|a Patel, Vishal M.
|e author.
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| 245 |
1 |
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|a Sparse Representations and Compressive Sensing for Imaging and Vision
|c by Vishal M. Patel, Rama Chellappa.
|h [electronic resource] /
|
| 264 |
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1 |
|a New York, NY :
|b Springer New York :
|b Imprint: Springer,
|c 2013.
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| 300 |
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|a X, 102 p. 41 illus.
|b online resource.
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| 490 |
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|a SpringerBriefs in Electrical and Computer Engineering,
|x 2191-8112
|
| 505 |
0 |
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|a Introduction -- Compressive Sensing -- Compressive Acquisition -- Compressive Sensing for Vision -- Sparse Representation-based Object Recognition -- Dictionary Learning -- Concluding Remarks.
|
| 520 |
# |
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|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.
|
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|a Engineering.
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|a Computer vision.
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1 |
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|a Engineering.
|
| 650 |
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|a Signal, Image and Speech Processing.
|
| 650 |
2 |
4 |
|a Image Processing and Computer Vision.
|
| 700 |
1 |
# |
|a Chellappa, Rama.
|e author.
|
| 710 |
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|a SpringerLink (Online service)
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|t Springer eBooks
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|z 9781461463801
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|a SpringerBriefs in Electrical and Computer Engineering,
|x 2191-8112
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|a Engineering (Springer-11647)
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