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The application of discrete wavelet transforms to SAR image processing Zeng, Zhaohui

Abstract

Synthetic aperture radar (SAR) is a very efficient instrument for obtaining a. better understanding of the earth's environment. SAR, data represents an important source of information for a large variety of scientists around the world. However, the acquiring mechanism of SAR is quite different from other sensors, such as optical sensors. It brings some unique properties of SAR image data which decides that conventional image processing technique may fail to obtain satisfactory result or have to be modified to adapt the application of SAR image data. The objective of this thesis work is to investigate the potential of discrete wavelet transforms (DWT) for SAR image processing. The emphasis is placed on speckle noise reduction and SAR image compression, which are the two of the most popular application fields of DWT to image processing in the current literature. Two new algorithms for speckle reduction have been developed: a Bayesian method based on the statistical model and wavelet extrema based on the local property of wavelet coefficients, and have been applied to both airborne and spaceborne SAR images. The comparison of their results to some existing well known methods show their advantages on both the visual and numerical sides. In addition, simultaneous speckle reduction and data compression can significantly improve the compressibility of SAR images. The modified SPIHT aJgorithm has been applied to SAR image coding. The effectiveness of this strategy has been proven from the comparison to the method without speckle reduction and classic efficient wavelet compression algorithms.

Item Metadata

Title
The application of discrete wavelet transforms to SAR image processing
Creator
Zeng, Zhaohui
Publisher
University of British Columbia
Date Issued
1999
Description
Synthetic aperture radar (SAR) is a very efficient instrument for obtaining a. better understanding of the earth's environment. SAR, data represents an important source of information for a large variety of scientists around the world. However, the acquiring mechanism of SAR is quite different from other sensors, such as optical sensors. It brings some unique properties of SAR image data which decides that conventional image processing technique may fail to obtain satisfactory result or have to be modified to adapt the application of SAR image data. The objective of this thesis work is to investigate the potential of discrete wavelet transforms (DWT) for SAR image processing. The emphasis is placed on speckle noise reduction and SAR image compression, which are the two of the most popular application fields of DWT to image processing in the current literature. Two new algorithms for speckle reduction have been developed: a Bayesian method based on the statistical model and wavelet extrema based on the local property of wavelet coefficients, and have been applied to both airborne and spaceborne SAR images. The comparison of their results to some existing well known methods show their advantages on both the visual and numerical sides. In addition, simultaneous speckle reduction and data compression can significantly improve the compressibility of SAR images. The modified SPIHT aJgorithm has been applied to SAR image coding. The effectiveness of this strategy has been proven from the comparison to the method without speckle reduction and classic efficient wavelet compression algorithms.
Extent
21368284 bytes
Genre
Thesis/Dissertation
Type
Text
File Format
application/pdf
Language
eng
Date Available
2009-07-03
Provider
Vancouver : University of British Columbia Library
Rights
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.
DOI
10.14288/1.0065356
URI
http://hdl.handle.net/2429/10152
Degree
Master of Applied Science - MASc
Program
Electrical and Computer Engineering
Affiliation
Applied Science, Faculty of; Electrical and Computer Engineering, Department of
Degree Grantor
University of British Columbia
Graduation Date
1999-11
Campus
UBCV
Scholarly Level
Graduate
Aggregated Source Repository
DSpace

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For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.