Restoration of Wavelet-Compressed Images and Motion Imagery

Abstract

This technical report investigates the characteristics of compression noise in images and motion imagery compressed by scalar quantization of the data's two- or three-dimensional wavelet transform coefficients. Such quantization noise is both experimentally and theoretically shown to be spatially varying in the pixel domain, with statistical correlations between the errors at the pixel locations. A quantization noise covariance matrix is presented that can find use in general restoration scenarios where the observed image or images have been compressed by scalar quantization of the data's wavelet coefficients. Several restoration examples, including de-blurring for the single-image case and temporal filtering for the motion-imagery case, are provided to demonstrate the quantization noise model's advantage over the common assumption of independent and identically distributed noise. (7 tables, 19 figures, 29 refs.)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2004
Accession Number
ADA420892

Entities

People

  • Mark A. Robertson

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

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

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Algorithms
  • Coefficients
  • Computational Science
  • Covariance
  • Distribution Functions
  • Filtration
  • Gaussian Distributions
  • Gaussian Noise
  • Image Processing
  • Probabilistic Models
  • Probability
  • Probability Distribution Functions
  • Probability Distributions
  • Random Variables
  • Three Dimensional
  • Two Dimensional

Fields of Study

  • Engineering
  • Physics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Image Processing and Computer Vision.