An application of a gradient relaxation method to noisy infrared images.

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Author
McDougall, James Chauncy
Date
1987-06Advisor
Lee, Chin-Hwa
Second Reader
Therrien, Charles W.
Metadata
Show full item recordAbstract
Image segmentation is an essential preliminary step in
automatic pictorial pattern recognition and scene analysis
problems. The objective of segmentation techniques is to
partition an image into regions or components. The purpose
of this thesis is to analyze a segmentation technique called
gradient relaxation. The gradient relaxation method is a
viable method in segmenting objects within an image. The
gradient relaxation technique is applicable to images having
unimodal distributions. This method is applied to noisy
infrared images in an attempt to detect and classify the
target. The method allows for an easy selection of a
threshold value which may be required for other types of
image processing on the image. The main issue is to examine
the effectiveness of this technique applied to noisy
infrared images from uncooled focal plane array sensor
having unimodal distributions. The technique was able to
extract the target in the image, producing a homogeneous and
uniform region for most of the cases studied. A target
which was fragmented into several parts because of the noise
is not detectable. The technique could be implemented in
hardware and applied to the inputs of a classification
system for detectable objects in noisy infrared images.
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This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.Collections
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