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Lars Arge

Cleaning Massive Sonar Point Clouds

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

  • Department of Computer Science

We consider the problem of automatically cleaning massive sonar data point clouds, that is, the problem of automatically removing noisy points that for example appear as a result of scans of (shoals of) fish, multiple reflections, scanner self-reflections, refraction in gas bubbles, and so on.


We describe a new algorithm that avoids the problems of previous local-neighbourhood based algorithms. Our algorithm is theoretically I/O-efficient, that is, it is capable of efficiently processing massive sonar point clouds that do not fit in internal memory but must reside on disk. The algorithm is also relatively simple and thus practically efficient, partly due to the development of a new simple algorithm for computing the connected components of a graph embedded in the plane. A version of our cleaning algorithm has already been incorporated in a commercial product.

Original languageEnglish
Title of host publicationProceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems. GIS '10
Number of pages10
PublisherAssociation for Computing Machinery
Publication year2010
Pages152-161
ISBN (print)978-1-4503-0428-3
DOIs
Publication statusPublished - 2010
Event18th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2010) - San Jose, California, United States
Duration: 3 Nov 20105 Nov 2010

Conference

Conference18th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2010)
LandUnited States
BySan Jose, California
Periode03/11/201005/11/2010

    Research areas

  • MBES, noise removal, I/O-efficient algorithms, connected components

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