Heterogeneous Image Systems

Systems for processing, generating, and transmitting digital images
(image systems) often have hard constraints on compute performance,
latency, throughput, and costs. Typical examples are medical image
processing, computer games, or video compression on camcorders. In
order to fulfill these constraints often dedicated hardware
accelerators are used, as well as graphics processors (GPUs) or
digital signal processors (DSPs). The resulting image systems are
heterogeneous in two respects: First, within a system the computation
is spread to several components, second, there is a large
heterogeneous set of architectures on which different image
applications are executed. Both types of heterogeneity lead to very
interesting and important research problems, which are examined in the
graduate school. Three major topics will be considered: dedicated
hardware architectures for image systems, tools and methods for the
programming of heterogeneous image systems, and applications and
algorithms for heterogeneous image systems.

Image systems are of high importance, both in research and in
practice. Their planning, development and realization requires
comprehensive and interdisciplinary knowledge in soft- and hardware,
method and tool design, and algorithm development. The topic is very
appropriate for a graduate school, in particular in the research and
industrial environment of Erlangen. The doctoral candidates get a
comprehensive education, which is expanded in specialized problems
during the dissertation. PostDocs with larger scientific overview act
as multidisciplinary connectors. They qualify interdisciplinary and
gather teaching experience. The already existing focus of the topic in
the teaching program allows us to include qualified students into
research. Finally, Erlangen offers an industrial environment that will
give important suggestions for the research, but that will also
benefit from novel ideas as well as from highly qualified graduates.