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Low-complexity video coding via power-rate-distortion optimization

机译:通过功率率失真优化实现低复杂度视频编码

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Wireless multimedia sensor networks (WMSNs) have been potentially applicable for several emerging applications. The resources, i.e., power and bandwidth available to visual sensors in a WMSN are, however, very limited. Hence, it is important but challenging to achieve efficient resource allocation and optimal video data compression while maximizing the overall network lifetime. In this paper, a power-rate-distortion (PRD) optimized resource-scalable low-complexity multiview video encoding scheme is proposed. In our video encoder, both the temporal and interview information can be exploited based on the comparisons of extracted media hashes without performing motion and disparity estimations, which are known to be time-consuming. We present a PRD model to characterize the relationship between the available resources and the RD performance of our encoder. More specifically, an RD function in terms of the percentages for different coding modes of blocks and the target bit rate under the available resource constraints is derived for optimal coding mode decision. The major goal here is to design a PRD model to optimize a "motion estimation-free" low-complexity video encoder for applications with resource-limited devices, instead of designing a general-purpose video codec to compete compression performance against current compression standards (e.g., H.264/AVC). Analytic results verify the accuracy of our PRD model, which can provide a theoretical guideline for performance optimization under limited resource constraints. Simulation results on joint RD performance and power consumption (measured in terms of encoding time) demonstrate the applicability of our video coding scheme for WMSNs.
机译:无线多媒体传感器网络(WMSN)已潜在地适用于几种新兴应用。然而,WMSN中视觉传感器可用的资源,即功率和带宽非常有限。因此,在使整个网络寿命最大化的同时,实现有效的资源分配和最佳的视频数据压缩是重要但具有挑战性的。本文提出了一种功率率失真(PRD)优化的资源可缩放低复杂度多视点视频编码方案。在我们的视频编码器中,可以基于提取的媒体哈希值的比较来利用时间信息和采访信息,而无需执行运动和视差估计,这是费时的。我们提出一种PRD模型来表征可用资源与编码器的RD性能之间的关系。更具体地,导出针对块的不同编码模式的百分比和在可用资源约束下的目标比特率的RD函数,以用于最佳编码模式决策。此处的主要目标是设计PRD模型,以针对资源受限的设备优化“无运动估计”的低复杂度视频编码器,而不是设计通用视频编解码器以使压缩性能与当前压缩标准竞争(例如H.264 / AVC)。分析结果验证了我们PRD模型的准确性,该模型可以为有限资源约束下的性能优化提供理论指导。针对联合RD性能和功耗(以编码时间衡量)的仿真结果证明了我们的WMSN视频编码方案的适用性。

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