Enhancing Real-Time Motion Estimation through Approximate High-Level Synthesis

As newer video encoding standards are proposed, higher compression rates are attained at the cost of increasing computational complexity. Thus, achieving real-time video encoding for higher resolutions and frame rates becomes challenging, especially when considering costs in area and energy. Approximate accelerators can be used to alleviate the costs of critical kernels, such as motion estimation, but their design becomes costly when maintaining a short time-to-market is desirable, especially in a scenario of standards that evolve frequently. In this work, we propose the use of High-Level Synthesis (HLS) to quickly generate Pareto-optimal motion estimation approximate accelerators. We propose a throughput-aware approximate HLS tool able to attain area savings between 6% and 55% or improve the frame rate by between 5.5% and 78%, with PSNR reductions varying from 0.32 dB to 3.4 dB, respectively.