Photon-limited Sensing and Surveillance

Abstract

The goal of this work was to learn and exploit unknown spatio-temporal structure in online photon-limited sensing and surveillance data. Photon-limited imaging arises in a wide variety of applications of interest to the Air Force, including night vision, space weather, imaging through fog, and spectral imaging. The photon-limited video reconstruction problem is particularly challenging because (a) the limited number of available photons introduces intensity-dependent Poisson statistics which require specialized algorithms and analysis for optimal performance, (b) vast quantities of video data will be collected sequentially, necessitating fast online algorithms, and (c) unknown and changing environmental dynamics preclude classical methods based on known dynamical models. Many current systems sidestep photon limitations by artificially restricting the frame rate and resolution of the video, but sophisticated statistical methods allow dramatic increases in resolution and improved object identification and detection capabilities.

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Document Details

Document Type
Technical Report
Publication Date
Jan 29, 2015
Accession Number
ADA620166

Entities

People

  • Rebecca Willett
  • Robert Calderbank

Organizations

  • Duke University

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Compressed Sensing
  • Distance Learning
  • Filters
  • Filtration
  • Gaussian Noise
  • Image Processing
  • Image Reconstruction
  • Information Theory
  • Inverse Problems
  • Kalman Filters
  • Low Resolution
  • Night Vision
  • Sequential Monte Carlo Methods
  • Signal Processing

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Image Processing and Computer Vision.
  • Systems Analysis and Design

Technology Areas

  • Space
  • Space - Space Objects