High-speed Motion Estimation Architecture for Real-time Video Transmission

Abstract

Motion estimation (ME) process consumes up to 70% of the total encoding time of video transmission. Because it has a high coding efficiency and it is very scalable, the full search (FS) algorithm is considered to be the most popular ME algorithm. However, the main drawback of the FS algorithm is that it is computationally intensive. For this reason, FS is rarely used for real-time video coding. This paper proposes a simple and fast adaptive search window size (ASWS) algorithm that eliminates a significant amount of computations from the conventional FS algorithm. This is achieved by dynamically reducing the required search area for each reference block. Simulation results show that more than 94% of the candidate blocks are eliminated by our algorithm without significant loss in visual quality. This paper also presents an efficient and high-speed ME engine (MEE) architecture for the proposed ASWS algorithm. The MEE efficiently reuses the search area data to minimize the memory I/O while fully utilizing the available hardware resources. A smart processing element design along with an innovative data scheduling scheme allows the search area data to flow both horizontally and vertically, whereas the current block data remain stationary. This allows the proposed architecture a simple and highly regular dataflow through the core. Simulation results show that for a search range of [-16,+15] and a block size of 16×16, the proposed architecture performs the ME for 60 fps of 4CIF video at 100 MHz and easily outperforms many FS architectures.