Fast and energy-efficient approximate motion estimation architecture for real-time 4 K UHD processing

Abstract

Approximate computing techniques exploit the characteristics of error-tolerant applications either to provide faster implementations of their computational structures or to achieve substantial improvements in terms of energy efficiency. In video encoding, the motion estimation (ME) stage, including the Integer ME (IME) and the Fractional ME (FME) steps, is the most computational intensive task and it is highly resilient to controlled losses of accuracy. In accordance, this article proposes the exploitation of approximate computing techniques to implement energy efficient dedicated hardware structures targeting the motion estimation stage of current video encoders. The designed ME architecture supports IME and FME and is able to real-time process 4 K UHD videos (3840 × 2160 pixels) at 30 frames per second, while dissipating 108.92 mW. When running at its maximum operation frequency, the architecture can process 8 K UHD videos (7680 × 4320 pixels) at 120 frames per second. The solution described in this article presents the highest throughput and the highest energy efficiency among all state-of-the-art compared works, showing that the use of approximate computing is a promising solution when implementing video encoders in dedicated hardware.