28 February 2017 Underwater reflectance transformation imaging: a technology for in situ underwater cultural heritage object-level recording
Author Affiliations +
J. of Electronic Imaging, 26(1), 011029 (2017). doi:10.1117/1.JEI.26.1.011029
Abstract
There is an increasing demand for high-resolution recording of in situ underwater cultural heritage. Reflectance transformation imaging (RTI) has a proven track record in terrestrial contexts for acquiring high-resolution diagnostic data at small scales. The research presented here documents the first adaptation of RTI protocols to the subaquatic environment, with a scuba-deployable method designed around affordable off-the-shelf technologies. Underwater RTI (URTI) was used to capture detail from historic shipwrecks in both the Solent and the western Mediterranean. Results show that URTI can capture submillimeter levels of qualitative diagnostic detail from in situ archaeological material. In addition, this paper presents the results of experiments to explore the impact of turbidity on URTI. For this purpose, a prototype fixed-lighting semisubmersible RTI photography dome was constructed to allow collection of data under controlled conditions. The signal-to-noise data generated reveals that the RGB channels of underwater digital images captured in progressive turbidity degraded faster than URTI object geometry calculated from them. URTI is shown to be capable of providing analytically useful object-level detail in conditions that would render ordinary underwater photography of limited use.
David Selmo, Fraser Sturt, James Miles, Philip Basford, Tom Malzbender, Kirk Martinez, Charlie Thompson, Graeme Earl, George Bevan, "Underwater reflectance transformation imaging: a technology for in situ underwater cultural heritage object-level recording," Journal of Electronic Imaging 26(1), 011029 (28 February 2017). http://dx.doi.org/10.1117/1.JEI.26.1.011029
Submission: Received 30 June 2016; Accepted 2 February 2017
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KEYWORDS
Signal to noise ratio

Reflectivity

Cameras

Underwater imaging

RGB color model

Photography

Visualization

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