Return to search

Ship Detection and Property Extraction in Radar Images on Hardware

In this work we review the problem of radar imaging satellites' dependency on ground stations to transfer the image data. Since synthetic aperture radar images are very big, only ground stations are equipped to transfer that much data. This is a problem for maritime surveillance as it creates delay between the imaging and processing. We propose a new hardware algorithm that can be used by a satellite to detect ships and extract information about them, and since this information is smaller it can be relayed to reduce the delay significantly. For ship detection, an adaptive thresholding algorithm with exponential model is used. This algorithm was selected as it is the best fit for single-look radar images. For the property calculation, a data accumulating, single-look, connected component labeling algorithm is proposed. This algorithm accumulates data about the connected components, which is then used to calculate the properties of ships using image moments. The combined algorithm was then validated on Radarsat-2 images using Matlab for software and co-simulation for hardware. / Graduate

Identiferoai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/6499
Date21 August 2015
CreatorsKilinc, Koray
ContributorsGebali, Fayez, Li, Kin F.
Source SetsUniversity of Victoria
LanguageEnglish, English
Detected LanguageEnglish
TypeThesis
RightsAvailable to the World Wide Web, http://creativecommons.org/licenses/by-nc-nd/2.5/ca/

Page generated in 0.0016 seconds