Superresolution of Passive Millimeter-Wave Imaging

Abstract

In standard intensity imaging, the resolution is limited by the width of the aperture. The region of support of the autocorrelation of the pupil function is the measured spatial frequency bandwidth of the imaging system and thus determines the resolution limit. This relationship between the size of the pupil function and the resolution limit is generally taken to describe a fundamental limit for resolution. Contrary to conventional wisdom, the resolution is actually limited only for fields with zero higher-order cumulants. For fields with non-vanishing higher-order cumulants, higher resolution can be obtained by integrating higher powers of instantaneous intensity in the image plane and combining these images appropriately. The result is that resolution is limited only by the time required for the integral of the higher power of intensity to approximate the expected value. We demonstrate these claims and analyze the variance of the integrated intensity-squared image as a function of the temporal spectrum and integration time. Furthermore, various image restoration strategies are proposed to estimate the superresolved intensity image from the various measurements. Our simulations show imaging of spatial frequency information outside the support of the pupil function autocorrelation for non-Gaussian fields.

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Document Details

Document Type
Technical Report
Publication Date
Apr 28, 1998
Accession Number
ADA343682

Entities

People

  • Stanley J. Reeves

Organizations

  • Auburn University

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Bandwidth
  • Data Science
  • Digital Image Processing
  • Digital Images
  • Electrical Engineering
  • Frequency
  • Image Processing
  • Image Restoration
  • Information Processing
  • Intensity
  • Millimeter Waves
  • Order Statistics
  • Signal Processing
  • Standards
  • Statistics

Fields of Study

  • Physics

Readers

  • Image Processing and Computer Vision.
  • Statistical inference.

Technology Areas

  • 5G