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Application studies in the areas of image- and video-processing indicate that between 50%-80% of the power cost in these systems is due to data storage and transfers. This is especially true for multiprocessor realizations because conventional parallelization methods ignore the power cost and focus only on performance. However, the power consumption also heavily depends on the way a system is parallelized. To reduce this dominant cost, we propose to address the system-level storage organization for the multidimensional signals as a first step in mapping these applications, before the parallelization or partitioning decisions (in particular, before the hardware/software (HW/SW) partitioning, which is traditionally done too early in the design trajectory). Our methodology is illustrated on a parallel quadtree-structured difference pulse-code modulation video codec.