Abstract
A method for segmenting synthetic aperture radar (SAR) images has been developed to operate primarily in the frequency domain. It is based on and was tested against a similar method which involves isolating information of the frequency-domain image that defines unique textural features within a class. The comparison involved classifying four simple vegetation SAR scenes with both segmentation methods. A statistical test was then performed against the null hypothesis that the new textural segmentation method is as accurate or more accurate than the original method based on random pixel classification results. All tests concluded that the texture extraction methods are not statistically different Both methods were implemented on a mainframe computer and are computationally intensive, but the new method may be implemented optically more easily.
Library of Congress Subject Headings
Synthetic aperture radar; Image processing--Digital techniques
Publication Date
9-1-1992
Document Type
Thesis
Department, Program, or Center
Chester F. Carlson Center for Imaging Science (COS)
Advisor
Schott, John
Recommended Citation
Ehrhard, David G., "Applications of fourier-based features for classification of synthetic aperture radar imagery" (1992). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/2816
Campus
RIT – Main Campus
Comments
Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works. Physical copy available through RIT's The Wallace Library at: TK6592.S95 E37 1992