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Virginia Tech

Noise and Degradation Reduction for Signal and Image Processing via Non-adaptive Convolution Filtering

Abstract

dc:description.abstract

Noise and degradation reduction is of significant importance in virtually all systems where these phenomena are present, specifically in the fields of signal and image processing. The effect of image processing on target detection is of significant interest because noise and degradations can greatly reduce the effectiveness of detection algorithms, due to the presence of high intensity noise which is often mistaken as a target. In signal processing, noise in vibration data, or any time-series data, can reduce the accuracy of measurement and can prevent the passing of useful information. Many filters that have been developed are designed to reduce a single class of noise, such as Wiener and Frost filters. When these filters are applied to types of noise that they were not designed for, the effect of the noise reduction can be greatly reduced. The proposed Two-Stage Non-Adaptive Convolution (TSNAC) filter significantly reduces both additive and multiplicative noise in these two unique systems. The performance of these filters is compared through several Image Quality (IQ) metrics. It will be shown that the proposed TSNAC filter reduces noise and degradations more effectively in both SAR images and synthetic vibration data than the competing filters. It will show higher IQ scores, greater computational efficiency in target detection, and significant improvement in signal restoration of simulated vibration data.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Mechanical Engineering
Department dc:contributor.department
Mechanical Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2013

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Bjerke, Benjamin A.
Chair dc:contributor.committeechair
  • Roan, Michael J.
Committee members dc:contributor.committeemember
  • Leonessa, Alexander
  • Papenfuss, Cory M.

Subjects

dc:subject × 5

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:1525
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/23700

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Bjerke, Benjamin A.. Noise and Degradation Reduction for Signal and Image Processing via Non-adaptive Convolution Filtering. masters thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/23700