Comparative Analysis of Reconstructed Image Quality in a Simulated Chromotomographic Imager

Abstract

A hyperspectral chromotomographic instrument has been developed to determine the spatial and spectral distribution of a target. It does this by recording the dispersed images produced by a rotating direct vision prism with a high speed camera. The recorded images are processed through a tomographic reconstruction algorithm to produce a reconstructed hypercube. A physics-based system model was developed to investigate three areas. The first was how the prism angle selection and range of angles used impacted the reconstructed image quality. The second was an assessment of a new iterative reconstruction algorithm developed to remove artifacts produced in the Back Projection algorithm. The third area was how optical aberrations in the recorded images impacted the reconstructed image. The areas of investigation were completed using a new prism design because a distortion-like effect found in the current prism design. The majority of the image quality gains were accomplished in the first 30 projections used in the reconstruction. Provided at least 30 projections were used in the reconstruction the new algorithm, developed for this investigation, outperformed Back Projection in 15 of the 18 targets evaluated.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2014
Accession Number
ADA610217

Entities

People

  • Ryan L. Tervo

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Biomedical
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Artifacts
  • Cross Correlation
  • Detectors
  • Distortion
  • Focal Plane Arrays
  • Focal Planes
  • Frequency Domain
  • Geometry
  • Hyperspectral Imagery
  • Three Dimensional
  • Two Dimensional
  • United States
  • United States Government
  • X Rays
  • X-Ray Computed Tomography

Fields of Study

  • Physics

Readers

  • Computational Modeling and Simulation
  • Image Processing and Computer Vision.