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Bibframe Work

Title
Sparse representations and compressive sensing for imaging and vision
Type
Text
Monograph
Contribution
Patel, Vishal M. (Author)
Chellappa, Rama (Author)
Subject
Signal processing--Digital techniques--Mathematics (LCSH)
Computer vision--Mathematics (LCSH)
Language
English
Illustrative Content
Illustrations
Classification
LCC: TK5102.9 .P38 2013
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Supplementary Content
bibliography
Content
text
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.
Table Of Contents
Compressive Sensing
Compressive Acquisition
Compressive Sensing for Vision
Sparse Representation-based Object Recognition
Dictionary Learning
Concluding Remarks.
Authorized Access Point
Patel, Vishal M. Sparse representations and compressive sensing for imaging and vision
Admin Metadata
Generation Process: DLC marc2bibframe2 v2.5.0
Status: changed
Encoding Level: full
Identified By: bf:Local, 17572927
Change Date: 2016-08-15T16:09:52
Creation Date: 2012-12-26
Description Language: English
Description Modifier: United States, Library of Congress
Description Authentication:
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