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Improving Underwater Accuracy by Empirical Weighting of Image Observations
3D Optical Metrology (3DOM) unit, Bruno Kessler Foundation (FBK), Trento, Italy.
3D Optical Metrology (3DOM) unit, Bruno Kessler Foundation (FBK), Trento, Italy.
LSIS, I&M Team, Aix-Marseille Universite, Polytech Luminy, Marseille, France. (ICube Laboratory UMR 7357, Photogrammetry and Geomatics Group)
3D Optical Metrology (3DOM) unit, Bruno Kessler Foundation (FBK), Trento, Italy.
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2018 (English)In: ISPRS Technical Commission II Symposium 2018, ISPRS , 2018, Vol. XLII-2, p. 699-705Conference paper, Published paper (Refereed)
Abstract [en]

An underwater imaging system with camera and lens behind a flat portdoes not behave as a standard pinhole camera with additionalparameters. Indeed, whenever the entrance pupil of the lens is not incontact with the flat port, the standard photogrammetric model is notsuited anymore and an extended mathematical model that considers thedifferent media would be required. Therefore, when dealing with flatports, the use of the classic photogrammetric formulation represents asimplification of the image formation phenomenon, clearly causing adegradation in accuracy. Furthermore, flat ports significantly changethe characteristics of the enclosed imaging device and negativelyaffect the image quality, introducing heavy curvilinear distortionsand optical aberrations. With the aim of mitigating the effect ofsystematic errors introduced by a combination of (i) image qualitydegradation, induced by the flat ports, and (ii) a non-rigorousmodelling of refraction, this paper presents a stochastic model forimage observations that penalises those that are more affected byaberrations and departure from the pinhole model. Experiments werecarried out at sea and in pools showing that the use of the proposedstochastic model is beneficial for the final accuracy withimprovements up to 50%.

Place, publisher, year, edition, pages
ISPRS , 2018. Vol. XLII-2, p. 699-705
Series
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750, E-ISSN 2194-9034
Keywords [en]
underwater photogrammetry, image quality, bundle adjustment, image observation weighting
National Category
Computational Mathematics Probability Theory and Statistics
Research subject
Computer and Information Science; Mathematical Statistics
Identifiers
URN: urn:nbn:se:umu:diva-147868OAI: oai:DiVA.org:umu-147868DiVA, id: diva2:1207134
Conference
ISPRS Technical Commission II Symposium 2018, Riva del Garda, Italy, June 3-7, 2018
Available from: 2018-05-18 Created: 2018-05-18 Last updated: 2018-06-09

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Börlin, Niclas

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