Multichannel 2-D power spectral estimation and applications.
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Authors
El-Shaer, Hamdy Taha M.
Subjects
signal modeling
linear prediction
image coding
AR models
maximum likelihood method
spectral estimation
linear prediction
image coding
AR models
maximum likelihood method
spectral estimation
Advisors
Therrien, Charles W.
Fredricksen, Harold
Lewis, Peter A.W.
Ziomek, Lawrence J.
Moose, Paul H.
Date of Issue
1987-12
Date
December 1987
Publisher
Language
en_US
Abstract
Spectral estimation for multiple 2-D signals by model-based methods is developed. The procedures compute the entire spectral matrix of autospectra and cross spectra for the set of 2-D signals. Spectral analysis by autoregressive (AR) modeling is studied extensively. Specific differences between AR models for this problem and those for lower dimensional problems are highlighted. An extension of the Jackson-Chien method for combining estimates with single quadrant support is proposed and a method is developed for estimating the model parameters directly from the data (i.e. without prior estimation of a correlation matrix). A measure of the similarity of two spectral estimates based on the statistical divergence is proposed and used to compare various spectral estimates. A comprehensive set of experimental studies are presented showing the performance of the methods in estimating the autospectra and magnitude and phase of the cross spectra. The Maximum Likelihood Method (MLM) of spectral estimation is extended to the multichannel 2-D case. The properties are compared experimentally with the autoregressive methods. The Improved Maximum Likelihood Method (IMLM) is also developed for the multichannel case. Finally applications of multichannel 2-D spectral analysis models to image coding are presented.
Type
Thesis
Description
Series/Report No
Department
Electrical and Computer Engineering
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funding
Format
303 p.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
Copyright is reserved by the copyright owner