Search

Integer motion estimation (IME), which acts as a key component in video encoder, is to remove temporal redundancies by searching the best integer motion vectors for dynamic partition blocks in a macro-block (MB). Huge memory bandwidth requirements and unbearable computational resource demanding are two key bottlenecks in IME engine design, especially for large search window (SW) cases. In this paper, a three-level pipelined VLSI architecture design is proposed, where efficiently integrates the reference data sharing search (RDSS) into multi-resolution motion estimation algorithm (MMEA). First, a hardware-friendly MMEA algorithm is mapped into three-level pipelined architecture with neglected coding quality loss. Second, sub-sampled RDSS coupled with Level C + are adopted to reduce on-chip memory and bandwidth at the coarsest and middle level. Data sharing between IME and fractional motion estimation (FME) is achieved by loading only a local predictive SW at the finest level. Finally, the three levels are parallelized and pipelined to guarantee the gradual refinement of MMEA and the hardware utilization. Experimental results show that the proposed architecture can reach a good balance among complexity, on-chip memory, bandwidth, and the data flow regularity. Only 320 processing elements (PE) within 550 cycles are required for IME search, where the SW is set to 256 × 256. Our architecture can achieve 1080P@30 fps real-time processing at the working frequency of 134.6 MHz, with 135 K gates and 8.93 KB on-chip memory.

The aim of this paper is to investigate the existence of exponential attractors for lattice reaction-diffusion systems in weighted spaces $l_{\sigma}^{2}$ and for partly dissipative lattice reaction-diffusion systems in weighted spaces $l_{\mu}^{2}\times l_{\mu}^{2}$ , respectively. In contrast to the previous work by Abdallah in J. Math. Anal. Appl. 339, 217---224 (2008) and Commun. Pure Appl. Anal. 8, 803---818 (2009), we get the existence of exponential attractors for lattice dynamical systems in the weak topology spaces.