Low-complexity H.264/AVC motion compensated prediction for mobile video applications

The performance of the motion-compensated prediction (MCP) in video coding is degraded by aliasing due to spatial sampling. To alleviate this problem in H.264/AVC, a low-pass filter is used by the fractional-pel motion estimation (FME) to suppress the aliasing component. However, the FME demands higher computational complexity on H.264/AVC encoding. In this work, we first perform a joint quantization and aliasing analysis on the H.264/AVC MCP process and show that the impact of the aliasing component can be alleviated by the quantization process. Then, we propose a fast motion estimation (ME) algorithm that uses the FME and the integer-pel motion estimation (IME) adaptively. The adaptive FME/IME algorithm examines the coding modes of the reference block for the current coding block, and then decides whether the FME or the IME should be applied to the current coding block. Experimental results show that the proposed adaptive FME/IME algorithm can help the encoder generate a bit stream at much lower computational complexity with small degradation in the coding gain as compared with a pure FME algorithm.