Multi-level pipelined parallel hardware architecture for high throughput motion and disparity estimation in Multiview Video Coding

Bruno Zatt, Muhammad Shafique, Sergio Bampi, Jörg Henkel

Abstract: This paper presents a novel motion and disparity estimation (ME, DE) scheme in Multiview Video Coding (MVC) that addresses the high throughput challenge jointly at the algorithm and hardware levels. Our scheme is composed of a fast ME/DE algorithm and a multi-level pipelined parallel hardware architecture. The proposed fast ME/DE algorithm exploits the correlation available in the 3D-neighborhood (spatial, temporal, and view). It eliminates the search step for different frames by prioritizing and evaluating the neighborhood predictors. It thereby reduces the coding computations by up to 83% with 0.1 dB quality loss. The proposed hardware architecture further improves the throughput by using parallel ME/DE modules with a shared array of SAD (Sum of Absolute Differences) accelerators and by exploiting the four levels of parallelism inherent to the MVC prediction structure (view, frame, reference frame, and macroblock levels). A multi-level pipeline schedule is introduced to reduce the pipeline stalls. The proposed architecture is implemented for a Xilinx Virtex-6 FPGA and as an ASIC with an IBM 65nm low power technology. It is compared to state-of-the-art at both algorithm and hardware levels. Our scheme achieves a real-time (30fps) ME/DE in 4-view High Definition (HD1080p) encoding with a low power consumption of 81 mW.