Sparse Representations and Compressive Sensing for Imaging and Vision

by Vishal M. Patel, Rama Chellappa

Overview

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.

Product Details

ISBN-13:	9781461463818
Publisher:	Springer-Verlag New York, LLC
Publication date:	02/11/2013
Series:	SpringerBriefs in Electrical and Computer Engineering
Sold by:	Barnes & Noble
Format:	eBook
Pages:	102
File size:	3 MB

Table of Contents

Introduction.- Compressive Sensing.- Compressive Acquisition.- Compressive Sensing for Vision.- Sparse Representation-based Object Recognition.- Dictionary Learning.- Concluding Remarks.