Sparse representations and compressive sensing for imaging and vision
Author(s)
Bibliographic Information
Sparse representations and compressive sensing for imaging and vision
（Springerbriefs in electrical and computer engineering）
Springer, c2013
Available at / 11 libraries
-
No Libraries matched.
- Remove all filters.
Note
Includes bibliographical references (p. 95-102)
Description and Table of Contents
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.
Table of Contents
Introduction.- Compressive Sensing.- Compressive Acquisition.- Compressive Sensing for Vision.- Sparse Representation-based Object Recognition.- Dictionary Learning.- Concluding Remarks.
by "Nielsen BookData"