An Objective Evaluation of Four SAR Image Segmentation Algorithms

<p>Because of the large number of SAR images the Air Force generates and the dwindling number of available human analysts automated methods must be developed. A key step towards automated SAR image analysis is image segmentation. There are many segmentation algorithms but they have not been tested on a common set of images and there are no standard test methods. This thesis evaluates four SAR image scgmentation algorithms by running them on a common set of data and obj ectively comparing them to each other and to human segmentors. This objective comparison uses a multimetric approach with a set of master segmentations as ground truth. The metric results are compared to a Human Threshold which defines the performance of human segmentors compared to the master segmentations. Also methods that use the multimetrics to detemmine the best algorithm are developed. These methods show that of the four algorithms Statistical Curve Evolution produces the best segmentations; however none of the algorithms are superior to human segmentors. Thus with the Human Threshold and Statistical Curve Evolution as benchmarks this thesis establishes a new and practical framework for testing SAR image segmentation algorithms.</p><p>This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact and remains as true to the original work as possible. Therefore you will see the original copyright references library stamps (as most of these works have been housed in our most important libraries around the world) and other notations in the work.</p><p>This work is in the public domain in the United States of America and possibly other nations. Within the United States you may freely copy and distribute this work as no entity (individual or corporate) has a copyright on the body of the work.</p><p>As a reproduction of a historical artifact this work may contain missing or blurred pages poor pictures errant marks etc. Scholars believe and we concur that this work is important enough to be preserved reproduced and made generally available to the public. We appreciate your support of the preservation process and thank you for being an important part of keeping this knowledge alive and relevant.</p>