This work addresses the challenges of mapping imaging and computer vision applications to embedded multiprocessor systems. Even though there is an abundance of data parallelism available for typical algorithms in this application domain, it is far from trivial to exploit this parallelism because of complex interactions between different optimization techniques. Furthermore, a given optimal solution will only be optimal on a specific hardware platform. On different platforms, it will not only show inferior performance, but might in the worst case, if for example local memories are smaller, not...