Denoising of Acoustic Signals Using Wavelet/Wiener Based Techniques

Abstract

This thesis investigates the use of combined Wavelet decomposition and Wiener filtering for the removal of noise from underwater acoustic signals. Several Wavelet/Wiener based denoising techniques are presented and their performances compared. Performances of the denoising algorithms are compared to those of Wiener filter and wavelet thresholding implementation and demonstrate that Wavelet/Wiener based methods are also a viable tool for the denoising of acoustic data under more restrictive conditions.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1998
Accession Number
ADA349997

Entities

People

  • Coskun Cebeci

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Acoustic Signals
  • Algorithms
  • Bandwidth
  • Decomposition
  • Electrical Engineering
  • Engineering
  • Filters
  • Filtration
  • Fourier Analysis
  • Fourier Series
  • Frequency
  • Frequency Bands
  • Frequency Domain
  • Signal Processing
  • Simulations
  • Time Domain
  • Wavelet Transforms

Fields of Study

  • Engineering

Readers

  • Acoustical Oceanography.
  • Image Processing and Computer Vision.