Efficient parallel algorithms for synthetic aperture radar data processing using large-scale distributed frameworks
Name
Oskar Hint
Abstract
Processing radar satellite images is a considerable computing task due to large image sizes. Distributed computing can often be leveraged to speed up algorithms that are too time-consuming on a single machine. It is however unclear which radar image processing algorithms can be efficiently migrated to parallel environments and what is the proper way to implement them. Previous works have concentrated on parallel image processing as a general computing task but either the unique properties of radar images or newer distributed computing frameworks are not considered or only some specific algorithms have been examined. This thesis proposes a classification of radar image processing algorithms that can potentially be parallelized. Each class of algorithms is studied based on the properties of current popular distributed computing frameworks and file systems. Algorithms that best represent their respective classes are implemented using some concrete distributed computing framework. The classification simplifies the gauging of potential algorithms in terms of parallel speedup and provides general implementation steps, thus easing the task of leveraging distributed computing for radar image processing.
Graduation Thesis language
English
Graduation Thesis type
Bachelor - Computer Science
Supervisor(s)
Pelle Jakovits
Defence year
2015