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Proceedings Paper

Automated change detection for synthetic aperture sonar
Author(s): Tesfaye G-Michael; Bradley Marchand; J. Derek Tucker; Daniel D. Sternlicht; Timothy M. Marston; Mahmood R. Azimi-Sadjadi
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Paper Abstract

In this paper, an automated change detection technique is presented that compares new and historical seafloor images created with sidescan synthetic aperture sonar (SAS) for changes occurring over time. The method consists of a four stage process: a coarse navigational alignment; fine-scale co-registration using the scale invariant feature transform (SIFT) algorithm to match features between overlapping images; sub-pixel co-registration to improves phase coherence; and finally, change detection utilizing canonical correlation analysis (CCA). The method was tested using data collected with a high-frequency SAS in a sandy shallow-water environment. By using precise co-registration tools and change detection algorithms, it is shown that the coherent nature of the SAS data can be exploited and utilized in this environment over time scales ranging from hours through several days.

Paper Details

Date Published: 29 May 2014
PDF: 11 pages
Proc. SPIE 9072, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIX, 907204 (29 May 2014); doi: 10.1117/12.2053067
Show Author Affiliations
Tesfaye G-Michael, Naval Surface Warfare Ctr. Panama City Div. (United States)
Bradley Marchand, Naval Surface Warfare Ctr. Panama City Div. (United States)
J. Derek Tucker, Naval Surface Warfare Ctr. Panama City Div. (United States)
Daniel D. Sternlicht, Naval Surface Warfare Ctr. Panama City Div. (United States)
Timothy M. Marston, Univ. of Washington Applied Physics Lab. (United States)
Mahmood R. Azimi-Sadjadi, Colorado State Univ. (United States)


Published in SPIE Proceedings Vol. 9072:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIX
Steven S. Bishop; Jason C. Isaacs, Editor(s)

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