High Performance Computing for Visualisation and Image Analysis

  • Heiko Schröder
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5857)

Abstract

Visualisation of data is an area of increasing importance in a wide range of areas such as complex systems, simulation of large systems, seismic image analysis and medical applications. Image analysis has also increased in importance such as in automatic surveillance. In this presentation I will concentrate on techniques and applications I have been involved with or led. These are 1) The design of the PIPADS machine (Parallel Image Processing and Display System), which was designed to analyse and visualise seismic data as well as remote sensing data. 2) The design of a High Performance fault tolerant parallel computing system for the Singaporean satellite X-Sat, which is a remote sensing satellite equipped with a multi spectral camera. 3) The use of the COPACOBANA engine for computer tomography for the Australian Synchrotron, to produce a 10Kx10Kx4K 3D image out of 5K 10Kx4K projections. This engine has the additional particular feature that it is extremely energy efficient – a characteristic of increasing importance.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Heiko Schröder
    • 1
  1. 1.School of Computer Science & Information TechnologyRMIT UniversityMelbourneAustralia

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