Image Compression Research.

Abstract

The vast quantities and high generation rates of tactical imagery require very efficient data compression in order to conserve precious bandwidth for transmission and to limit the required storage volume for archiving. This report describes the results of efficiency and image quality comparisons for several transform image coding techniques. Research effort focused on developing the Singular Valve Decomposition (SVD) as an approach to image compression. Detailed comparisons were to the two-dimensional cosine transform, Hadamard transform and Karhunen-Loeve techniques. High and low altitude aerial imagery, and IR and SAR imagery were included. Images were coded with rates in the range .25 to 1.5 bits per pixel (bpp). (Original images were digitized at 8 bpp.) The order of performance, as measured by rms error (reconstructed image versus original) versus bpp, as well as by visual image quality judgements, was first, cosine and Karahunen-Loeve (nearly the same), second, SVD, and third, Hadamard. Computational burdens, however, are least for the Hadamard, intermediate for cosine and Karhunen-Loeve and most for the SVD technique.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1981
Accession Number
ADA110811

Entities

People

  • Michael S. Murphy

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Applied Mathematics
  • Artificial Intelligence
  • Coding
  • Communication Systems
  • Compression Ratio
  • Data Compression
  • Decoding
  • Digital Images
  • Image Compression
  • Image Processing
  • Pattern Recognition
  • Probability Density Functions
  • Random Variables
  • Statistical Analysis
  • Statistics
  • Two Dimensional

Readers

  • Radar Systems Engineering.
  • Wave Propagation and Nonlinear Chaotic Dynamics.