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 measurements...
| Main Author: | Patel, Vishal M. |
|---|---|
| Other Authors: | Chellappa, Rama., SpringerLink (Online service) |
| Format: | eBook |
| Language: | English |
| Published: |
New York, NY :
Springer New York : Imprint : Springer,
2013.
New York, NY : 2013. |
| Physical Description: |
1 online resource (x, 102 pages 41 illustrations). |
| Series: |
SpringerBriefs in electrical and computer engineering.
|
| Subjects: |
| Summary: |
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. |
|---|---|
| Item Description: |
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. Introduction -- Compressive Sensing -- Compressive Acquisition -- Compressive Sensing for Vision -- Sparse Representation-based Object Recognition -- Dictionary Learning -- Concluding Remarks. Includes bibliographical references. English. |
| Physical Description: |
1 online resource (x, 102 pages 41 illustrations). |
| Bibliography: |
Includes bibliographical references. |
| ISBN: |
9781461463818 1461463815 1461463807 9781461463801 9781299335493 1299335497 |
| ISSN: |
2191-8112. |