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Compressive Sensing for the Photonic Mixer Device Fundamentals, Methods and Results /

Miguel Heredia Conde aims at finding novel ways to fit the valuable mathematical results of the Compressive Sensing (CS) theory to the specific case of the Photonic Mixer Device (PMD).To this end, methods are presented that take profit of the sparsity of the signals gathered by PMD sensors. In his r...

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Main Author: Heredia Conde, Miguel. (Author, http://id.loc.gov/vocabulary/relators/aut)
Corporate Author: SpringerLink (Online service)
Language:English
Published: Wiesbaden : Springer Fachmedien Wiesbaden : Imprint: Springer Vieweg, 2017.
Edition:1st ed. 2017.
Subjects:
Optical data processing.
Data structures (Computer science).
Applied mathematics.
Engineering mathematics.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Data Structures and Information Theory.
Mathematical and Computational Engineering.
Online Access:https://doi.org/10.1007/978-3-658-18057-7
Table of Contents:
  • Phase-Shift-Based Time-of-Flight Imaging Systems
  • Fundamentals of Compressive Sensing
  • High Resolution Characterization of PMD Pixels
  • Compressive Sensing in Spatial and Time-Frequency Domains
  • CS-PMD: A Compressive Sensing ToF Camera based on the Photonic Mixer Device.

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