Date of Award

12-1990

Document Type

Thesis

Degree Name

Master of Science in Electrical Engineering

Department

Department of Electrical and Computer Engineering

First Advisor

David Meer, PhD

Abstract

This thesis investigated the potential of fractal dimension estimation for segmenting high resolution polarimetric synthetic aperture radar. The data used during this research were collected with the Advanced Detection Technology Sensor (ADTS) developed by Massachusetts Institute of Technology Lincoln Laboratory with Defense Advanced Research Projects Agency funding. ADTS is a fully polarimetric calibrated 35 GHz SAR with one foot impulse response. A method of applying the correlation dimension algorithm developed by Grassberger and Procaccia for estimating the dimension of time series data was implemented to estimate the correlation dimension of polarimetric SAR data. A threshold sensitivity study was performed to determine which combination of polarizations used to calculate the correlation dimension resulted in most accurately segmented image. Correlation dimension estimates were shown to be valid and robust features for segmenting ADTS imagery into culture, tree, field, and shadow regions. Simple thresholding and median filtering of correlation dimension estimates calculated from non-overlapping windows of ADTS imagery produced segmented imagery that was consistently over 90% accurate when using all four linear polarizations. An approach was implemented for automatically distinguishing between different classes of naturally occurring regions within the SAR image using correlation dimension estimates as input features to artificial neural networks.

AFIT Designator

AFIT-GE-ENG-90D-06

DTIC Accession Number

ADA230428

Comments

The author's Vita page is omitted

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