Metric Aspects of Digital Images and Digital Image Processing.

Abstract

The ability of human pointing in digitized aerial imagery is studied. Automated methods for extracting edge locations in digital imagery are determined with subpixel accuracy. An algorithm for automatically extracting cross targets from aerial imagery is developed and implemented. Crosses are recognized using a method based on Fourier descriptors. Precise locations of the crosses are determined by Fourier descriptions and further refined using a least squares adjustment model. Mean cross location errors are as low as 0.03 pixels. Metric distortions caused by digital image processing techniques are studied using the Fourier descriptor-least squares algorithms. Cross positions are 'shifted' by as much as 0.5 pixels when cosine compression is applied with a 16-fold bit reduction. Mean and median filters show little metric distortions. An isotropic median filter is developed. Resampling with various interpolation functions shows that metric distortion is lower when using bilinear interpolation as compared to nearest neighbor or bucubic interpolation.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1984
Accession Number
ADA147211

Entities

People

  • E. M. Mikhail
  • O. R. Mitchell

Organizations

  • Purdue University

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Aerial Photography
  • Artificial Intelligence
  • Change Detection
  • Civil Engineering
  • Computer Vision
  • Data Compression
  • Databases
  • Digital Data
  • Digital Images
  • Feature Extraction
  • Image Processing
  • Information Processing
  • Information Science
  • Pattern Recognition
  • Photographs
  • Two Dimensional

Readers

  • Computer Vision.
  • Image Processing and Computer Vision.
  • Radar Systems Engineering.