Optimization of the Adaptive Computationally-Scalable Motion Estimation and Compensation for the Hardware H.264/AVC Encoder

The adaptive computationally-scalable motion estimation algorithm and its hardware implementation allow the H.264/AVC encoder to achieve efficiencies close to optimal in real-time conditions. Particularly, the search algorithm achieves results close to optimum even if the number of search points assigned to macroblocks is strongly limited and varies with time. The architecture implementing the algorithm developed and reported previously takes at least 674 clock cycles to interpolate and load reference area, and the number cannot be decreased without decreasing the search range. This paper proposes some optimizations of the architecture to increase the maximal throughput achieved by the motion estimation system even four times. Firstly, the chroma interpolation follows the search process, whereas the luma interpolation precedes it. Secondly, the luma interpolator computes 128 instead of 64 samples per each clock cycle. Thirdly, the number of on-chip memories keeping interpolated reference area is increased accordingly to 128. Fourthly, some modules previously working at the base frequency are redesigned to operate at the doubled clock. Since the on-chip memories do not store fractional-pel chroma samples, their joint size is reduced from 160.44 to 104.44 kB. Additional savings in the memory size are achieved by the sequential processing of two reference-picture areas for each macroblock. The architecture is verified in the real-time FPGA hardware encoder. Synthesis results show that the updated architecture can support 2160p@30fps encoding for 0.13 mu m TSMC technology with a small increase in hardware resources and some losses in the compression efficiency. The efficiency is improved when processing smaller resolutions.