Paper
21 October 2010 Image analysis for water surface and subsurface feature detection in shallow waters
Charles R. Bostater Jr., James Jones, Heather Frystacky, Mate Kovacs, Oszkar Jozsa
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Abstract
Carefully collected airborne imagery demonstrates the ability to see water surface features as well as shallow bottom features such as submerged vegetation and manmade targets. Traditional photogrammetric imagery and airborne digital imagery both suffer from a loss in image clarity due to a number of factors, including capillary and small gravity waves, the water column or in-situ constituents. The use of submerged as well as surface man-made calibration targets deployed during airborne or in-situ subsurface image acquisitions forms a preliminary basis for correcting imagery in order to improve subsurface and surface features and their detection. Methods presented as well as imagery at 490 nm, 532 nm and 698-700 nm clearly show subsurface features in shallow waters. The techniques utilized include the use of large frame cameras with photogrammetric films in combination of special filters, such as a Wratten # 70, in order to provide narrower spectral features near the vegetative "red edge" to be used to improve interpretation of hyperspectral push broom imagery. Combined imagery from several sensors and platforms, including autonomous underwater vehicles, form the basis of data fusion for surface and subsurface automatic feature extraction. Data presented from a new hyperspectral imaging system demonstrates the utility of sub-meter hyperspectral imagery for use in subsurface feature detection.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Charles R. Bostater Jr., James Jones, Heather Frystacky, Mate Kovacs, and Oszkar Jozsa "Image analysis for water surface and subsurface feature detection in shallow waters", Proc. SPIE 7825, Remote Sensing of the Ocean, Sea Ice, and Large Water Regions 2010, 78250H (21 October 2010); https://doi.org/10.1117/12.870728
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Cited by 5 scholarly publications.
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KEYWORDS
Cameras

Water

Hyperspectral imaging

Sensors

Feature extraction

Reflectivity

Vegetation

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