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Next-generation mobile devices will continue to demand high processing power for imaging applications. The expected performance is in the class of supercomputers, but delivered with limited energy and memory bandwidth for embedded systems. This article advocates a streaming computation model that leverages the deterministic access patterns in imaging applications to deliver the necessary processing throughput. A reconfigurable datapath connects a set of functional units, forming a computation pipeline to offer energy efficiency. The architecture and implementation of a stream processor are presented along with the memory subsystem to support stream data transfers. The results show speedup ranging from a factor of 2 to 28 for imaging applications, offering favorable comparison against scalar processors.