Support for Implications of Compressive Sensing Concepts to Imaging Systems

Abstract

Compressive Sensing (CS) has emerged as field of study that has the potential to revolutionize the sensor industry, with applications that span across commercial, defense, security and medical domains. While the mathematics is well understood, in recent years there has been a surge of interest in harnessing the potential of CS to design real-world systems that provide significant benefits in reducing hardware cost/complexity, improve the data processing efficiency, and enabling new sensing capabilities that cannot be achieved using conventional techniques. The purpose of the Incubator was to seek answers about what is "real" in CS. Hence, the questions on the table were:1. Are there any concrete applications where CS has offered a quantifiable advantage over other State of the Art techniques? 2. What are the underlying factors that lead to these advantages? Are these factors transferable to other important applications? 3. When there is a clear benefit, what are the challenges that are holding it back from implementation? 4. What technology advances are required to make it a compelling technique to help meet current and future needs?

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Document Details

Document Type
Technical Report
Publication Date
Aug 02, 2015
Accession Number
AD1001330

Entities

People

  • Abhijit Mahalanobis
  • Joe Mait
  • Mark Neifeld
  • Ravi Athale

Organizations

  • Optica

Tags

Communities of Interest

  • Advanced Electronics
  • Air Platforms
  • Autonomy
  • Biomedical
  • Sensors
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • 4G Wireless Networks
  • Compressed Sensing
  • Detection
  • Detectors
  • Electrical Engineering
  • Engineers
  • Image Processing
  • Information Processing
  • Information Theory
  • Jet Propulsion
  • Military Research
  • National Security
  • Processing Equipment
  • Signal Processing
  • Spectroscopy
  • Students
  • Target Recognition

Readers

  • Defense Technology Research and Development.
  • Image Processing and Computer Vision.
  • Systems Analysis and Design