Automated Change Detection for Synthetic Aperture Sonar
NAVAL SURFACE WARFARE CENTER PANAMA CITY DIV FL
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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.
- Numerical Mathematics
- Optical Detection and Detectors
- Active and Passive Radar Detection and Equipment