With the increasing use of multi-core microprocessors and hardware accelerators in embedded media processing systems, there is an increasing need to discover coarse-grained parallelism in media applications written in C and C++.  Common versions of these codes use a pointer-heavy, sequential programming model to implement algorithms with high levels of inherent parallelism.  The lack of automated tools capable of discovering this parallelism has hampered the productivity of parallel programmers and application-specific hardware designers, as well as inhibited the development of automatic parallelizing compilers. Automatic discovery is challenging due to shifts in the prevalent programming languages, scalability problems of analysis techniques, and the lack of experimental research in combining the numerous analyses necessary to achieve a clear view of the relations among memory accesses in complex programs.  This paper is based on a coherent prototype system designed to automatically find multiple levels of coarse-grained parallelism.  It visits several of the key analyses that are necessary to discover parallelism in contemporary media applications, distinguishing those that perform satisfactorily at this time from those that do not yet have practical, scalable solutions.  We show that, contrary to common belief, a compiler with a strong, synergistic portfolio of modern analysis capabilities can automatically discover a very substantial amount of coarse-grained parallelism in complex media applications such as an {MPEG-4} encoder. These results suggest that an automatic coarse-grained parallelism discovery tool can be built to greatly enhance the software and hardware development processes of future embedded media processing systems.