Data Compression and Elementary Encoding of Wavelet Coefficients

Abstract

Two elementary algorithms are introduced for image compression each of which is based on efficient, lossless encoding of quantized bi-orthogonal wavelet coefficients. Application of this type of algorithm is applied to several standard test images using regular and hyperbolic wavelet bases, and comparisons are given to Shapiro's EZW algorithm. Peak signal to noise ratio improvements typically of 0.6-0.8 dB are demonstrated. Generalizations of this type of algorithm to non-square images and higher dimensions are also briefly described.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1997
Accession Number
ADA640181

Entities

People

  • Andrey D. Andreev
  • Robert C. Sharpley
  • Zhenguang Gao

Organizations

  • University of South Carolina

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Coders
  • Coding
  • Coefficients
  • Compression
  • Data Compression
  • Data Sets
  • Frequency
  • Image Compression
  • Image Processing
  • Information Theory
  • Mathematics
  • Random Variables
  • Standards
  • Three Dimensional
  • Two Dimensional
  • Wavelet Transforms

Readers

  • Calculus or Mathematical Analysis
  • Image Processing and Computer Vision.