A new global alignment approach for underwater optical mapping

Lately, underwater vehicles have become important tools for exploration, monitoring and creation of maps of the seabed. Within mapping applications, the maps obtained from optical data are becoming essential in different study areas such as biological, geological and archaeological surveys, or in de...

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Detalles Bibliográficos
Autores: Elibol, Armagan, García Campos, Rafael, Grácias, Nuno Ricardo Estrela
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2011
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10256/10200
Acceso en línea:http://hdl.handle.net/10256/10200
Access Level:acceso embargado
Palabra clave:Seguiment ambiental
Environmental monitoring
Fons marins
Ocean bottom
Imatges -- Processament
Image processing
Vehicles submergibles
Submersibles
Descripción
Sumario:Lately, underwater vehicles have become important tools for exploration, monitoring and creation of maps of the seabed. Within mapping applications, the maps obtained from optical data are becoming essential in different study areas such as biological, geological and archaeological surveys, or in detection of benthic temporal changes. However, the underwater medium is very challenging for optical sensors and does not allow the area of interest to be imaged in a single image. Therefore, image mosaicing methods are necessary. Although recent advances in detection of correspondences between images have resulted in highly effective image registration methods, global alignment methods are still needed to obtain a globally coherent mosaic. In this paper, we propose a new global alignment method which works on the mosaic frame and does not require non-linear optimisation. Additionally, a simple image rectifying method is presented to reduce the down-scaling effect which might occur when minimising errors defined in the mosaic frame. Moreover, this rectifying method can also be seen as an alternative and straightforward way of incorporating different sensor information if available. The proposed framework has been tested with underwater image sequences. The resulting method is faster than its counterparts while providing the same level of registration quality