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Related Concept Videos

Computed Tomography01:10

Computed Tomography

Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
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Imaging Biological Samples with Optical Microscopy

Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...

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Related Experiment Video

Updated: May 22, 2026

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging
08:55

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

Published on: July 12, 2022

Computational ghost imaging for remote sensing.

Baris I Erkmen1

  • 1Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, California 91109, USA. baris.i.erkmen@jpl.nasa.gov

Journal of the Optical Society of America. A, Optics, Image Science, and Vision
|May 8, 2012
PubMed
Summary
This summary is machine-generated.

Computational ghost imaging, a novel active imaging technique, can capture an object's Fourier transform for remote sensing. This study analyzes its performance under atmospheric turbulence and noise, finding it advantageous in specific scenarios.

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Area of Science:

  • Optics and Photonics
  • Remote Sensing Technologies
  • Computational Imaging

Background:

  • Computational ghost imaging (CGI) utilizes structured illumination and a single-pixel detector.
  • It offers potential for remote sensing applications by capturing spatial Fourier transforms.
  • Understanding CGI performance under real-world conditions is crucial.

Purpose of the Study:

  • To analyze the performance of a CGI architecture.
  • To determine image signature, resolution, and signal-to-noise ratio under practical constraints.
  • To compare CGI with conventional active imaging.

Main Methods:

  • Developed a CGI architecture to acquire 2D spatial Fourier transforms.
  • Analyzed performance considering atmospheric turbulence (Kolmogorov spectrum), background radiation, and detector noise.
  • Investigated a bistatic imaging geometry and short-exposure intensity averaging.

Main Results:

  • Quantified the resolution impact of nonuniform atmospheric turbulence.
  • Demonstrated that short-exposure intensity averaging can mitigate turbulence-induced resolution loss.
  • Identified key performance differences between CGI and conventional active imaging.

Conclusions:

  • CGI exhibits a distinct performance profile compared to conventional active imaging.
  • Specific scenarios exist where CGI theoretically outperforms traditional methods.
  • The study provides insights for optimizing CGI in challenging remote sensing environments.