Stochastic Determination of Optimal Wavelet Compression Strategies.

Abstract

Wavelet theory provides an attractive approach to signal and image compression. This work investigates a new approach for wavelet transform coefficient selection for efficient image compression. For a desired image compression ratio (50:1), wavelet scale thresholds are derived via a multiagent stochastic optimization process. Previous work has demonstrated an interscale relationship between the stochastically optimized wavelet coefficient thresholds. Based on the experimental results, a deterministic wavelet coefficient selection criterion is hypothesized and the constants of the equation statistically derived. Experimental results of the stochastic optimization and deterministic approaches are compared and contrasted with results from previously published wavelet coefficient threshold strategies.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1995
Accession Number
ADA299868

Entities

People

  • D. E. Waagen
  • J. D. Argast
  • J. R. Mcdonnell

Organizations

  • Naval Command, Control and Ocean Surveillance Center

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Coefficients
  • Compression
  • Compression Ratio
  • Computer Programming
  • Data Compression
  • Data Science
  • Equations
  • Evolutionary Algorithms
  • Genetic Algorithms
  • Image Compression
  • Image Reconstruction
  • Information Science
  • Optimization
  • Regression Analysis
  • Statistical Analysis
  • Wavelet Transforms

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Vision.
  • Mechanical Engineering/Mechanics of Materials.