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Self-Adaptive Algorithmic/Architectural Design for Real-Time, Low-Power Video Systems

机译:实时,低功耗视频系统的自适应算法/架构设计

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With reference to video motion estimation in the framework of the new H.264/AVC video coding standard, this paper presents algorithmic and architectural solutions for the implementation of context-aware coprocessors in real-time, low-power embedded systems. A low-complexity context-aware controller is added to a conventional Full Search (FS) motion estimation engine. While the FS coprocessor is working, the context-aware controller extracts from the intermediate processing results information related to the input signal statistics in order to automatically configure the coprocessor itself in terms of search area size and number of reference frames; thus unnecessary computations and memory accesses can be avoided. The achieved complexity saving factor ranges from 2.2 to 25 depending on the input signal while keeping unaltered performance in terms of motion estimation accuracy. The increased efficiency is exploited both for (ⅰ) processing time reduction in case of software implementation on a programmable platform; (ⅱ) power consumption reduction in case of dedicated hardware implementation in CMOS technology.
机译:参照新的H.264 / AVC视频编码标准框架中的视频运动估计,本文提出了在实时,低功耗嵌入式系统中实现上下文感知协处理器的算法和体系结构解决方案。低复杂度上下文感知控制器被添加到常规的全搜索(FS)运动估计引擎中。当FS协处理器工作时,上下文感知控制器从中间处理结果中提取与输入信号统计相关的信息,以便根据搜索区域大小和参考帧数自动配置协处理器本身。因此可以避免不必要的计算和存储器访问。根据输入信号的不同,所获得的复杂度节省系数范围为2.2至25,同时在运动估计精度方面保持了不变的性能。在(ⅰ)减少在可编程平台上实现软件的处理时间方面,都利用了提高的效率; (ⅱ)在CMOS技术中使用专用硬件的情况下降低了功耗。

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