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Associative processors are single-instruction multiple-data-based architectures that provide huge parallelism which can be very useful for processing video in real time. This paper describes architectural requirements for video and shows that associative processors are ideally suited for applications involving video. Some routines like discrete cosine transforms (DCTs) lack required parallelism and their implementation becomes critical for the overall performance of the processor for video. We present three different approaches for computing two-dimensional DCT on associative processors and discuss their implementation details. Many methods like conditional execution of DCT, have been suggested in literature for power efficiency. In this paper, we discuss integration of these techniques in our implementation. Finally, performance of Associative processors is compared with that of RISC and DSP processor and show that associative processors are better suited for processing video both in terms of speed and power.