Wavelet Shrinkage and Denoising

Abstract

Introduction to Wavelet Shrinkage and Denoising * Procedure for wavelet shrinkage * Why Wavelet Shrinkage Works * Two methods of Wavelet Shrinkage * An image is often corrupted by noise in its acquisition and transmission stage. * Noises are normally created when scanning images to produce digital images, recording a voice to an audio file, and even transmitting digital image often produce Noise. * This noise can be random or white noise with no coherence or coherent noise introduced by device mechanism * Wavelet shrinkage is a signal denoising technique based on the idea of thresholding the wavelet coefficients. * Denoising is the process of removing noise from a signal. * Wavelet coefficients having small absolute values are considered to encode very fine details of the signal. * Wavelet shrinkage denoising should not be confused with smoothing, Whereas smoothing removes high frequencies and retains low ones, denoising attempts to remove whatever noise is present and retain whatever signal is present regardless of the signal's frequency content.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2009
Accession Number
ADA535692

Entities

People

  • Brian Dadson
  • Lynette Obiero

Organizations

  • Virginia State University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Acquisition
  • Audio Files
  • Coefficients
  • Digital Images
  • Education
  • Estimators
  • Frequency
  • Gaussian Noise
  • Images
  • Information Operations
  • Iterations
  • Noise
  • Operations Research
  • Professional Development
  • Wavelet Transforms
  • White Noise

Readers

  • Image Processing and Computer Vision.
  • Powder metallurgy of Titanium alloys.