Efficient Algorithms for Large-Scale Image Analysis [Elektronische Ressource] / Jan Wassenberg. Betreuer: Peter Sanders

Efficient Algorithms forLarge-Scale Image Analysiszur Erlangung des akademischen Grades einesDoktors der Ingenieurwissenschaftender Fakultät für Informatikdes Karlsruher Instituts für TechnologiegenehmigteDissertationvonJan Wassenbergaus KoblenzTag der mündlichen Prüfung: 24. Oktober 2011Erster Gutachter: Prof. Dr. Peter SandersZweiter Prof. Dr.-Ing. Jürgen BeyererAbstractThe past decade has seen major improvements in the capabilitiesand availability of imaging sensor systems. Commercial satellitesroutinely provide panchromatic images with sub-meter resolution.Airborne line scanner cameras yield multi-spectral data with aground sample distance of 5 cm. The resulting overabundance ofdata brings with it the challenge of timely analysis. Fully auto-mated processing still appears infeasible, but an intermediate stepmight involve a computer-assisted search for interesting objects.This would reduce the amount of data for an analyst to examine,but remains a challenge in terms of processing speed and workingmemory.This work begins by discussing the trade-offs among the varioushardware architectures that might be brought to bear upon theproblem. FPGA and GPU-based solutions are less universal andentail longer development cycles, hence the choice of commoditymulti-core CPU architectures. Distributed processing on a cluster isdeemed too costly.