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High performance filtering for big datasets from Airborne Laser Scanning with CUDA technology

Abstract

There are many studies on the problems of processing big datasets provided by Airborne Laser Scanning (ALS). The processing of point clouds is often executed in stages or on the fragments of the measurement set. Therefore, solutions that enable the processing of the entire cloud at the same time in a simple, fast, efficient way are the subject of many researches. In this paper, authors propose to use General-Purpose computation on Graphics Processing Units (GPGPUs) to process the big datasets obtained from ALS. GPGPU handles computation for computer graphics using GPUs (Graphic Processing Units). This study was based on programming model Compute Unified Device Architecture (CUDA), which facilitates the development of applications in GPUs. CUDA programming was used to carry out the filtration based on adaptive TIN model method in the initial stage of the processing of big ALS dataset. Results of the analysis showed that GPGPU can be used for the filtration of ALS point clouds and significantly speeds up calculations for big dataset.

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Authors (3)

  • Photo of dr inż. hab Wioleta Błaszczak-bąk

    Wioleta Błaszczak-bąk dr inż. hab

  • Photo of dr hab. inż. Artur Janowski

    Artur Janowski dr hab. inż.

    • University of Warmia and Mazury
  • Photo of  Piotr Srokosz

    Piotr Srokosz

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Details

Category:
Articles
Type:
artykuły w czasopismach
Published in:
SURVEY REVIEW no. 50, pages 262 - 269,
ISSN: 0039-6265
Language:
English
Publication year:
2018
Bibliographic description:
Błaszczak-Bąk W., Janowski A., Srokosz P.: High performance filtering for big datasets from Airborne Laser Scanning with CUDA technology// SURVEY REVIEW -Vol. 50,iss. 360 (2018), s.262-269
DOI:
Digital Object Identifier (open in new tab) 10.1080/00396265.2016.1264180
Verified by:
Gdańsk University of Technology

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