Paper
23 May 2011 Seabed change detection in challenging environments
Cameron A. Matthews, Daniel D. Sternlicht
Author Affiliations +
Abstract
Automatic Change Detection (ACD) compares new and stored terrain images for alerting to changes occurring over time. These techniques, long used in airborne radar, are just beginning to be applied to sidescan sonar. Under the right conditions ACD by image correlation-comparing multi-temporal image data at the pixel or parcel level-can be used to detect new objects on the seafloor. Synthetic aperture sonars (SAS)-coherent sensors that produce fine-scale, range-independent resolution seafloor images-are well suited for this approach; however, dynamic seabed environments can introduce "clutter" to the process. This paper explores an ACD method that uses salience mapping in a global-to-local analysis architecture. In this method, termed Temporally Invariant Saliency (TIS), variance ratios of median-filtered repeat-pass images are used to detect new objects, while deemphasizing modest environmental or radiometric-induced changes in the background. Successful tests with repeat-pass data from two SAS systems mounted on autonomous undersea vehicles (AUV) demonstrate the feasibility of the technique.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Cameron A. Matthews and Daniel D. Sternlicht "Seabed change detection in challenging environments", Proc. SPIE 8017, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVI, 80170P (23 May 2011); https://doi.org/10.1117/12.881644
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Image filtering

Environmental sensing

Image processing

Target detection

Digital filtering

Automatic target recognition

Image resolution

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